KR20160064128A - Distributed data system with document management and access control - Google Patents

Abstract

A data management system and method includes a cloud-based platform coupled to a system of agents or folks hosted on a client device. The platform does not store the actual data, but instead uses the metadata provided by the agent to track the location of all data in the system and to manage the distributed storage, movement, and processing of the actual data in the agent. In doing so, the platform uses the agent's local repository to poll the repository networked with the "virtual cluster ". The agent collectively performs data monitoring, storage and transmission or movement and data processing operations as indicated by the platform, as described in the detailed description. Agents include agents hosted or connected to a processor-based device, agents hosted on devices in a local area network, agents hosted on devices in a wide area network, agents hosted on mobile devices, and agents hosted on cloud-based devices do.

Description

[0001] DISTRIBUTED DATA SYSTEM WITH DOCUMENT MANAGEMENT AND ACCESS CONTROL WITH DOCUMENT MANAGEMENT AND ACCESS CONTROL [0002]

Related Application

This application claims priority from U.S. Patent Application Serial No. 61 / 877,585 filed on September 13, 2013.

The present application is a continuation-in-part of U.S. Patent Application No. 13 / 738,796, filed January 10, 2013.

Technical field

The embodiments described herein relate to data processing, and more particularly to distributed storage and processing.

Customer-provided equipment (CPE) has been deployed to include cloud-based services to increase productivity, reduce support costs, and reduce upfront investment as cloud- Solution. Considering that local / cloud impacts existing investments and has less risk than complete migration to the cloud, a hybrid solution combining both CPE and cloud solutions is rapidly being adopted. Conventional cloud services include personal synchronous and shared services, online backup and large file transfer services. While these conventional cloud services focus on providing online storage, the ever-increasing number of connected computers, devices and websites has allowed users of these services to synchronize and access their recent files via multiple devices or through websites It means that you continue to have difficulties in doing so. In addition, enterprise users need a relatively high level of security to protect their business data, prevent eye-catching security intrusions, and the long-term viability of cloud storage providers to address issues related to transport storage and services to the cloud Lt; / RTI > As a result, there is a need for a cloud service with a concise approach for synchronizing and accessing files across multiple devices, while focusing on local data storage and peer-to-peer transport with water at a relatively higher level of security .

Include by reference

Each of the patents, patent applications and / or publications mentioned in this specification is herein incorporated in its entirety by reference to the same extent as if each individual patent, patent application and / or publication were specifically and individually incorporated by reference, .

1 is a block diagram of a system including a platform and an agent in an embodiment.
2 is a block diagram of an embodiment, a system including a group of independent agents and a platform coupled to a networked agent group.
3 is a block diagram of a system including multiple agents and platforms included within an organization in an embodiment;
4A is a block diagram of an exemplary system that includes an platform and an agent in an embodiment.
Figure 4B is another block diagram of an exemplary system including an platform and an agent, in an embodiment.
5 is an exemplary block diagram related to file synchronization between a platform and an agent in an embodiment;
Figure 6 is an exemplary flow chart associated with an agent, platform, and database in an embodiment.
Figure 7 is an exemplary flow chart associated with the use of synchronization targets to scan and synchronize libraries in an embodiment.
8 is a block diagram of a platform including a policy database and a rules engine in an embodiment.
9 is a block diagram illustrating metadata separated from other platform configurations in an embodiment.
Figure 10 shows, in an embodiment, the connection type of the platform.
11 shows, in an embodiment, a P2P connection type.
Figure 12 shows an exemplary screen of a management console in an embodiment.
Figure 13 shows, in an embodiment, an exemplary embodiment that includes file synchronization control.
Figure 14 illustrates an exemplary screen including security activation monitoring and notification in an embodiment.
FIG. 15 illustrates an exemplary screen including a document audit trail in an embodiment.
Figure 16 shows an exemplary screen, including an example of a file search and classification, in an embodiment.
Figure 17 shows an exemplary screen, including an example of controlled user sharing, in an embodiment.
Figure 18 illustrates, in an embodiment, an exemplary screen including remote device management and geolocation services.
Figure 19 illustrates an exemplary screen that includes, in an embodiment, selection of a storage location.

A data management system and method is disclosed that includes a cloud-based platform or engine coupled to a system of agents or folders hosted on a client device. The platform of one embodiment does not store actual data and instead uses the metadata provided by the agent to track the location of all data in the system and to manage the distributed storage, movement and processing of the actual data among the agents. As such, the system of one embodiment uses local storage at the agent to poll the networked storage into a "virtual cluster ". Agents collectively monitor, store and transport or move data, as described in the detailed description herein, and perform data processing operations as directed by the platform. An agent in one embodiment may be a processor-based device (e.g., a personal computer (PC), a tablet computer, a server computer, a network-attached storage (NAS) device, an Apple computer, a mobile device, an iOS device, An agent hosted in a device in a network (LAN), an agent hosted in a device in a wired network (WAN), an agent hosted in a mobile device, and a host device coupled to a cloud-based device (e.g., server, storage device, Agents, but are not limited thereto.

Although the detailed description of this specification includes many specifics for the purposes of illustration, many variations and modifications to the detailed description below will be apparent to those skilled in the art within the scope of the embodiments described herein. Accordingly, the following illustrative embodiments are intended to be limited, without departing from the generality of the claimed invention.

FIG. 1 is a block diagram of a system including an embodiment 120 in which a platform 110 and an agent 120 are shown. In such an embodiment, the platform connects to and / or includes a plurality of databases 130, as described in the detailed description herein. A plurality of client devices 140, each containing or hosting an agent, are connected to the platform and the database through a network connection, and receive and execute work tasks indicated by the platform using the database.

2 is a block diagram of an embodiment, a system including a group of independent agents and a platform coupled to a networked agent group. The platform of this embodiment connects to and / or includes a plurality of databases as described in detail herein. The client device is connected to the platform through a network connection. The first group of client devices 210 includes a plurality of client devices, each of which includes or hosts one agent and is connected to the platform independently via a network connection. The second group of client devices 220 includes a plurality of client devices each comprising an agent and independently connected to the platform and further forming a peer network (e.g., LAN, WAN, etc.), wherein , Peer-to-peer communication 230 is supported between agents.

3 is a block diagram of a system including multiple agents and platforms included within an organization in an embodiment; The platform may connect to and / or include various databases, as described in detail herein. The organization includes a plurality of groups (e.g., Group 1 through Group M, where M is any number) and each group includes several users (e.g., User 1 to User N, where N is any number) do. Each of the users of the organization includes some device (e.g., device P in device 1, where P is any number), and each device includes or hosts an agent connected to the platform via network coupling. The organization also includes an administrator console connected to the platform and enables an administrator to access the device according to the layer. The platform includes controls or rules that control access to data according to the organization, and the console console provides access to controls or rules whereby the administrator installs and maintains the rules (e.g., , Add, delete, modify, etc.).

In an example of such an organization, the agent is instructed by a command received from the platform, executes it, and each agent is hosted on a device registered to the user. Each user is a subset of a group, and each group is a subset of one organization. In each device, the agent indexes the contents of a memory contained in or accessible by the corresponding device, and provides metadata of the memory content to the platform. The console provides administrative control over rules that control access to data according to the organization. For example, an administrator can generate a rule that specifies that an organization can not contain any files larger than 10MB in size. The administrator can generate another rule that specifies that group 1 can not include any music or video files. Another embodiment rule specifies that group 2 can not contain any files marked as secret.

4A is a block diagram of an exemplary system that includes an platform and an agent in an embodiment. Figure 4B is another block diagram of an exemplary system including an platform and an agent, in an embodiment. Figures 4A and 4B are collectively referred to as "Figure 4 ". The platform uses knowledge of the data accessible by each of the agents obtained through the metadata to create or generate jobs and to assign jobs to the agents. Eventually, the agent performs tasks assigned to them by the platform and provides the platform with information about their data and the tasks performed. As an agent of one embodiment performs the tasks indicated by the platform, they are neither an application nor a user.

The platform includes and / or is connected to various databases. For example, the platform includes an agent database that is a list of all agents that can be used for the platform and the respective information of each agent. In addition to the agent database, the platform includes a database for tracking the location of all data in the system and for use by the agent in exchanging information for managing the distributed storage, movement and processing of the actual data . The database includes the agent database, library database, target database, and task database described above. Each agent may have one or more libraries representing their local disks or storage depots, the library database comprising a list of storage depots available to the corresponding agent, the storage depot being capable of reading and / or But is not limited to, any device (e.g., disk or disk drive, network mount point, hard drive, flash drive, storage storage service, etc.) The platform and each agent include a library of systems including a list of system libraries and a corresponding agent of each of the systems accessible to each library.

The target database includes a list of targets that are a collection of libraries (e.g., which should be synchronized) for which a particular task should be performed. The target database contains a list of targets that are a collection of libraries on which a particular task (e.g., synchronization) will be performed. The target is used by an agent to perform a task, and the target corresponds to one or more libraries and is used to perform a task or task on library content. In addition, the platform generates a task database for each agent, and tasks to be accomplished by corresponding agents in the task database are tasks. The task database includes a description of each of the tasks to be performed by an agent together with all the information required by the agent to perform the task. The database is described in detail below.

One embodiment of the platform is a universal synchronization (sync) engine that forms a grid through coupling between a platform and a plurality of agents, the platform serving as a master controller for agents. The platform is connected to one or more databases in the cloud and the database includes information received from an agent that contains data (e.g., metadata) about the location and status of all data in the grid for which the platform is responsible. Wherein the agent is an independently functioning entity that is hosted or installed on a particular device or computer to communicate with the platform and interact with the platform and other agents to form a grid, They work in concert to achieve the task.

In operation, the agent is hosted or installed on one device, and the agent is responsible for performing tasks or tasks assigned by the platform. The platform knows the identity and location of all the agents to which the platform is associated and the data that each agent is accessing. The agent is not an application, but instead is an agent of a platform that communicates with the platform and other agents over an encrypted channel, which performs operations as directed by the platform. In general, the platform generates and includes a target for which such a platform is responsible, and the platform assigns a task or task to the agent to cause the agent to achieve the goal. The agent also does not require any knowledge of the objectives corresponding to the tasks to which each agent or any other agent is assigned.

The platform of one embodiment does not store actual data in a database of one embodiment, but instead stores metadata corresponding to the data it is responsible for. As a result, because the platform only stores metadata, the agent acts as a distributed data storage storage entity in which the actual data is stored. The platform provides more than a file-level understanding of the data using metadata for bit-level understanding of the stored data at the agent. The metadata is received from each agent and is generated by the agent from data that each agent is responsible for. In generating the metadata, each agent scans the files requested by the platform. For each file, the scanning includes generating a fragment or configuration of data from the data forming the file by separating the file into variable size fragments, referred to herein as blobs. The blob is generated using a data fingerprinting algorithm that generates a portion of the data having a variable size between a pre-specified minimum and maximum length, as described in the following detailed description . Because the embodiments described herein generate blobs from the contents of one file and the blob represents the contents of the file, the terms "file (s)" and "blob (s)" are used interchangeably herein .

When generating a blob, a description of the blob is generated, the blob contains the value of the hash at a point that is cut off or separated from the rest of the file, and the hash for the complete content of the blob An offset value based on the breakpoint for the blob, and a size (e.g., length) of the blob. The complete content hash of the blob (blob hash, or "hash") serves as a unique identifier for the blob. In addition, the complete list of blobs that constitute the contents of one file is hashed (cash), giving a unique identifier for the entire file content, which is a hash of the content hash and the name hash (fash) . The hash of one embodiment further includes a hash of the file name, a file path (pash), and a hash of the file metadata (e.g., file name, size, date, location, etc.) (mash).

These various hashes are generated by each of the agents for each of the data files that each agent is responsible for and delivered to the platform, as described in detail below. The platform may generate a record for each of the files to include information of these various hashes. The platform uses the information or state of the data reported by the agent to the platform and included in these records to determine the state of the data and determines which agent has a version of the data that is out of date due to modification of the data Let the file versions be adjusted among the agents. The platform then generates a task with an agent that needs to update one or more files with the most recent version of the file, as described herein.

Thus, using the metadata, the platform maintains a master index of the data in the cloud and uses the target to read the master index or library of the agent to determine the location of various pieces of data associated with each target , Issues or generates jobs to identify inconsistencies or differences in the data and to eliminate identified inconsistencies or differences. Instead of being anonymous, since an agent of one embodiment is known and instructed by the platform, and only has the identity established in the platform and exchanges content with another agent controlled by such identity , Which is opposed to a peer-to-peer system.

The platform is efficient at delivering as little data as possible between peers as directly as possible. Further, the above embodiment of the present disclosure uses only the knowledge gathered by the platform of all the data locations together with the mutual cooperation processing between the agents, so as to move only the data that needs to be moved, Data, thereby providing a bandwidth that is relatively greater than the bandwidth of any one agent when operating independently. Thus, the platform of one embodiment provides data ubiquity by providing efficient storage, delivery, and global data mobility.

The system of the present invention provides hashing and block-level delivery of data among devices through the use of the blob. The block-level transfer only needs to update the changed data blocks in the devices, thus supporting efficient synchronization of the files as the data changes. The block-level further propagates the non-sequence file transfer because the blocks are moved and then reassembled once the data is hashed to form blocks, thereby eliminating the need for sequence file transfer. Similarly, embodiments support a reduction in data upload / download times, since blobs can be delivered from one or more other devices to any device that needs them simultaneously or nearly simultaneously. In addition, when a file is needed by a particular device in the grid and exists in more than one other device in the grid, different blocks can be delivered simultaneously from these multiple devices, ).

The platform directs such work by distributing work to agents in the grid, generating tasks or work items for a particular agent, and delivering such work items to the agent. A work item is delivered to the agent along with a completion condition for the work item. Such an embodiment is non-limiting. An agent in one embodiment is a flexible client that executes tasks or work items assigned to them by the platform.

In one embodiment, the work item assigned to the agent instructs the agent to scan or monitor the directory or folder in the memory device accessible by the agent and causes the agent to continue to report changes to any files in the directory or folder . Such a work item is used by the platform to initially receive metadata of a file corresponding to the agent if registration of the agent is made on the platform. Thus, in response to a change to a file, the scan job causes the agent to report any changes in the file's blob or metadata to the platform, To assign tasks to them. In addition, the platform of one embodiment is used to distribute logic for a new function to one or more agents. Thus, if the platform requires an agent to provide new functionality, the logic to enable such functionality can be passed to the appropriate agent by the platform.

Tasks or work items of an embodiment generated by the platform and assigned to each agent for execution include scanning, erasing, writing and uploading. An agent regressively monitors a file system or directory and views all changes to a file as a platform (for example, modifying a file, adding to a file, deleting a file, renaming a file, etc.) The scan task is executed. Reporting of such a change includes locating the modified file in the local database, and the metadata of the local database is then provided to the platform.

The described task of an embodiment includes the recording of a blob, as will be described in detail below. The present invention is not limited to such an embodiment. The agent performs the noted tasks by one or more file blobs from a first location (e.g., source device) to a second location (e.g., destination device). Each of the first and second locations may be located at a location in the storage device (e.g., from a first location on the computer hard disk to a second location on the computer hard disk), a location on another storage device in the same domain, (E.g., from a file system of one agent to a cloud-based storage, from a file system of the first agent through peer-to-peer communication, etc.) File system). Thus, the source of one embodiment may be any of the agent file systems in a cloud-based or network-based storage device.

A work item is delivered to the agent along with the completion condition for such work item, as described above. The completion condition associated with a recording work item includes reclaiming the blob or configuration needed to complete the recording, and the overwritten blob or configuration is the correct file. If the condition that the overwritten blob is the correct file is not met, then this same reporting is provided to the platform.

The agent performs an upload task by copying the blob from one agent to a cloud-based storage device. As a result, when a new file is placed in the agent's file system, the agent reports the addition of the file to the platform, and the platform assigns a job to the agent to transfer the file blob to the cloud- Make copies. In response, the agent determines if a new file exists in the cloud-based database, and if not, copies the file to the cloud-based database.

In one embodiment, the work item includes three steps including queued, pending, and completed (successfully or unsuccessfully). The platform keeps track of the states of the files corresponding to each agent by tracking the steps of the work items assigned to each agent.

To maximize communication efficiency between the platform and the agent, some information is stored between the platform and the agent. For example, an agent of one embodiment polls the platform to identify a new work item assigned to such an agent through the work database, and periodically polls the work database for assigned work items And store it locally. This reduces the amount of communication between the server and the server needed to download the agent and work item to the agent. Similarly, when a new file is identified at an agent, the new file is written to the agent's local library database, which is periodically copied to the batch at the platform. This eliminates the need for agents and / or platforms to perform file transfers each time a new file occurs. Also, as will be described in detail herein, the blobs of embodiments of the present invention support differential file transfer, and at least some of the information used to track the location of blobs and their presence in the system, Agent.

With respect to the recovery of the information required by an agent to perform the work task assigned by the platform, the agent may use the agent to identify the location of the information needed to complete a task that is not currently in the file owned by the agent And one layer. The layer of one embodiment includes an agent that initially probes the local memory and subsequently uses peer-to-peer communication to recover the necessary information that is located in a file that belongs to a peer but is not locally discovered. The agent recovers a cloud-based storage device (e.g., Amazon S3, etc.) or another remote storage storage entity when the necessary information is not locally discovered and is not located with the peer.

When peer-to-peer communication is used to obtain the necessary files, the platform provides the agent with a list of peer agents possessing the necessary files, but is not limited to this implementation. The list of peer agents provided by the platform is an ordered list, thereby allowing the agent to contact the peer agent using the order of the list, but the list of alternative embodiments may not be ordered.

With reference to FIG. 4B, the agent of the embodiment includes a number of threads or configurations that execute in parallel to provide the functionality of the agent. For example, a provider thread recovers a work item designated for an agent from a work item database of the platform, and locally provides or stores the work item database. The runner thread monitors the agent's local work item database, polls the work item individually from the local work item database, marks the item as pending in the local work item database, and sends the item to the appropriate task execution thread , And the written task is provided as a recording thread). When a task execution thread completes execution of a task received from a runner thread, it reports the state of execution (e.g., successful completion, failed completion, reason for unsuccessful completion, etc.) to the runner thread, And reports such state information back to the local work item database. An update thread monitors the local work item database for items marked complete, and reports the status information of the completed work items back to the platform. The responding platform updates the platform database appropriate for the work completed by the agent.

The platform of one embodiment operates using metadata of the data corresponding to each of the agents connected to such a platform, which is reported to the platform by each agent, as described herein. To create the metadata for the platform, the agent scans all the files they have in the folder to be synchronized. The agent creates or generates fragments or configurations of data from the data that make up the file by dividing the files into variable sized fragments that are blobs. The blobs are generated using fingerprinting algorithms and are represented by their blob hash, bash, referred to herein as bash. In particular, the agent generates a blob by executing a fast-window checksum on a predetermined number of bytes. One embodiment creates data portions having a variable size that is between a minimum length and a maximum length specified in advance.

The process of dividing files into constituent parts, referred to as fingerprints, includes executing a hash algorithm on a slice of data, which has a specific pattern of data (e.g., 12 "0" bit sequences; "0" bit sequence, six "1" bit sequences, etc.). The "size" of each piece is determined by setting the hash string, since 12-bit contiguous strings occur less frequently and thus generate a longer data slice than a 3-bit contiguous string. The fingerprint determines the boundaries of data blocks within a file and these boundaries are used to determine the common block or portions between two or more files.

A hash is created for each byte in a file using a hash algorithm in a sliding window of a predetermined size. For example, in one embodiment, the hash is generated against each byte in the file using a BUZ hash algorithm in a 48-byte window, and the application result of the hash algorithm is a 64-bit number. When the hash has a particular value (e.g., 12 bits or less and all are "0" bits). This is called a match value in the present specification, and one break is generated at this point in the file. The match value in one embodiment is generated, for example, when 12 bits or less of the window is a "0" bit.

When a blob is generated, the blob is truncated from the remainder of the file or hash value at a separate point, a hash of the complete content of the blob, an offset value based on the breakpoint of the blob, (E. G., Length) of the blob is generated. The hash function of the embodiment used to hash the complete contents of the blob is a skein cryptographic hash function (the internal state size is 512 bits and produces an output of 160 bits) . The hash of the complete content of the blob serves as a unique identifier for the blob. A file is reported or described as a list of all blobs containing such a file, and such a list of file hashes serves as the manifest of the corresponding file content.

The blob of one embodiment is stored in a central storage storage entity, but is not limited to such an implementation. In doing so, the platform directs each of the agents to forward a blob that is not previously reported by any agent to a central cloud-based storage entity; As an example, the central storage device may include an Amazon Simple Storage Service (S3). Thus, all blobs are stored locally in one or more agents and stored in central storage. Subsequently, an agent reports the blob and the platform directs the agent to forward the blob to the central storage if the blob is not previously reported by another agent.

In addition to the above-described bases, the system of one embodiment includes a number of different hashes for use in describing data in the system. For example, a complete list of the blobs that make up one file content is hashed as described above to generate a unique identifier for the complete file. Such a hash identifier of the complete file is called a content hash (cash) and allows a quick comparison to determine whether the two files contain the same content.

Another hash of one embodiment includes a combined hash of the content hash and the name hash, and is referred to herein as a file hash (fash). The file thus identifies the contents of the file at a particular location.

One embodiment of the hash includes a path hash and a metadata hash. The path hash or file path hash is called a path, and is a file name and a hash of the path of the file. A metadata hash called a mash is a hash of file metadata (e.g., file name, size, date, location, etc.). The hash described herein is generated by the agent and is passed to the platform, and is not limited to such an implementation.

An alternative embodiment uses hashing to form data blocks as described, and stores each block with version information. This enables versioning so that such versioning information is used to reassemble the data to produce an older version of the file.

Using a hash of one embodiment, a record is created on the platform for each file, and all records for all files include cache, cache, pass, and mash as well as all bash of the file. The library database includes these records of each file, but such embodiments are not limited to inclusion of these records in the library database. The platform uses the state of the information or data reported by the agent and included in these records to determine which agent has an out of date data version due to change or new data, To match the file version. The platform uses a fash (hash of file content and file name) to determine the status of the file and whether a file reported by one agent is the most recent version of the file. The platform then generates a task with an agent that needs to update one or more files with the latest version of the file.

Each of the agents first queries a local copy of the file manifest and, as directed by the platform to locate the particular data or blob, the blob having a particular hash corresponding to the data is stored in the local storage < RTI ID = 0.0 > So that it can be used in the device. When the agent can not find the file, it tries to find the file at a peer agent using a peer-to-peer protocol. When using the peer-to-peer protocol, the agent causes the agent to selectively look up the file using the list information of the agent with the file, and an alternative embodiment includes one or more layers for finding data, To-peer protocol.

Peer-to-peer communication is supported among the agents of one embodiment, and in this way, each agent reports the private IP address and the port it listens to the platform. In addition, such a platform observes the ports of each of the agents at a public IP address and at the time the agent reports the personal information (e.g., during registration of the agent, etc.). The platform generates and maintains a list of all agents along with the private IP address and port and the public IP address and port of each agent. Subsequently, when the first agent wants to establish peer-to-peer communication with the second agent, the first agent makes a query and receives the public and private IP addresses and ports of the second agent from the platform, Using such public and private information to try to connect to both.

Peer-to-peer communication between agents of an embodiment is encrypted using a RAS algorithm for public-key encryption, but is not limited to this implementation. The encryption in one embodiment does not hold or store all the keys locally within the grid, and therefore no entity outside the grid can access the unencrypted data. Further, additional data security is realized because no completion file is stored on the platform.

In one example involving encrypted peer-to-peer communication between agents, a second agent B desiring to communicate with the first agent A sends data for use in symmetric encryption between the agents A and B Thereby generating a random secret S used for encryption. The second agent B uses the public key of the first agent A to encrypt the secret S, recover it from the platform, and provide the encrypted secret S to the platform where it is stored. The second agent B is communicated to a first agent that establishes a communication session using a session ID, and in response, the first agent A fetches the encrypted secret S from the platform and sends the secret S Encrypt. Such a secret is later used by the first agent A and the second agent B to form an encrypted communication channel for peer-to-peer communication.

With reference to FIG. 4, this is a block diagram of an embodiment system that includes a platform and an agent, which generates or creates a task and assigns such a task to an agent, as described in detail herein . These agents then assign tasks assigned to them by the platform. The agent then performs the tasks assigned to them by the platform and provides the platform with the information of their data and the tasks performed. Since an agent of one embodiment performs the tasks indicated by the platform, they are neither an application nor a user. In operation, each agent is registered with the platform using a passport before it can be used for operation. In one embodiment, a received passport at the platform includes a key and information identifying a corresponding agent. The platform includes a list of all agents available to the platform and associated information of each of the agents, wherein the agents are located in the agent database by the platform as soon as they are registered with the platform.

In addition to the agent database, an embodiment platform includes and is coupled to a number of other databases in the cloud, wherein an agent and platform of one embodiment are connected to the database and exchange information using the database. The database is not limited to an agent database as described above, but includes a library database and a target database. Each of the agents may have one or more libraries representative of their local disks or storage devices, and the library database includes a list of storage devices available to the corresponding agent. The target database includes a list of targets that are a collection of libraries (e.g., synchronized) in which a particular task is performed.

With respect to the library database, each of the agents identifies a storage storage mount point, referred to herein as a library. The mount may include, but is not limited to, a disk or disk drive, a network mount point, a hard drive, a flash drive, and any device for which the agent is allowed read and / Do not. The platform and each agent include a global library database containing a list of libraries of systems, each corresponding to an agent of the system across each library.

In addition, each agent provides information about the contents of each library through the use of a periodic " snapshot " or by scanning each of the libraries, and the agent and platform use the information of the snapshot Track current status. The library database allows inquiries to find each of the libraries in the grid and identifies each agent capable of accessing the library. Such an architecture allows the agent and platform to know that each accesses the same library if they each access a library with a particular identity. Thus, each of the libraries is provided separately and separately in the library database. Each of the platforms and agents of an embodiment includes an entire library database including all library information of the grid, but is not limited to such an embodiment. Optionally, the platform comprises an entire library database of all libraries in the grid, each of which includes a local library database containing information of the libraries accessible by a particular agent.

The platform also includes a target used by the agent to perform the task. The goal is to handle only the library instead of handling agents, mounts, tasks, and so on. A target corresponding to one or more libraries is used to perform operations or tasks on the contents of the library. Further, a library may correspond to multiple goals in one embodiment.

The platform of one embodiment includes a task database corresponding to each agent, and the agent receives the task database from the platform. The platform generates a task database for each agent, and places the task to be accomplished by the corresponding agent in the task database. Such a task database includes a description of each of the tasks to be performed by the agent along with all the information needed by the agent to perform the task. Any task located within the task database by the platform is dynamically modified or deleted in response to other tasks performed in the grid. For example, if a task is placed in the job database "to rename file A to file B," and subsequently file B is to be renamed to file C, then the platform " Modify the above operation to "Naming again with C". Also, tasks that are no longer useless are removed from the task database.

In one embodiment, an agent provides information about its capabilities to the platform. Optionally, the platform includes or generates a capability database that includes overall information of all agent capabilities of the grid.

The agents receive tasks assigned by the platform via the task assignment or their respective task databases, as described above. Each discrete work item in the job database includes a verb describing the action to be taken by the agent. For example, a task that can be executed by an agent of one embodiment includes scanning, deleting, recording, uploading, and the like. A work item is passed to the agent along with a completion condition for that work item.

For example, the scan task may include reporting to the platform the current state of a file in an agent library, and the platform may include a platform change (e.g., adding a file, deleting a file, etc.) And reporting changes made to any file in the library.

Another task is to record a list of blobs where the agent finds the appropriate file, breaks the file into blobs, encrypts those blobs, and forms a file on an object storage device such as a cloud-based storage device Or an upload task. When data is written to an object storage device, the data is addressed so that a hash of the blob is passed to the object storage device and subsequently used to refer to the blob / data (i.e., Hash).

A task of one embodiment also includes locating one or more blobs of a file and copying the blobs from a first location (e.g., a source device) to a second location (e.g., a destination device). In response to the received written task, one agent attempts to find the blob in the corresponding agent library. If the blob is not found, then the agent tries to find the blob at the peer agent reporting that it has the blob. If the blob is not found in a peer agent, then the agent recovers the file from the object storage device (e.g., a cloud-based storage device). When the entire file has to be written, the list of blobs is reported or recorded as a manifest of the file.

With reference to Figure 4, an embodiment of operation includes synchronization of a document at a device / agent in response to a determination that the version of the document is not the latest version found in another device / agent. After registering agent AGENT_X using passport. The agent is instructed to perform a scan to generate and provide a library file containing the library LIBRARY_X contents of the agent to the platform. To start the scan, the platform adds the scan task to the task database (e.g., WORK AGENTX) for a particular agent (e.g., AGENT JX), and the platform does all the work required to synchronize the file Write to the operations database for the agent.

The library LIBRARY_X contains metadata about the files on the mount accessible by AGENTJX, and includes metadata defining a subset of files by library identifier or filter. Thus, the library includes metadata of a set of files residing on one mount. The scan is a job that is constantly performed to generate metadata provided to the platform, where the metadata represents the contents of such a library (e.g., LIBRARY_X) for each "scanned" library. Consequently, generally, a mirror of each of the libraries in each of the agents is generated and placed in the library database of the platform so that the library database contains the filtered metadata based on the application of a particular filter as a mount accessible by each agent do.

 As a result of the operation applied to all agents accessible by the platform, the platform includes metadata of the contents of all the files of the agent it accesses. The platform also includes a "sync" purpose for LIBRARY_X and LIBRARY_Y of another agent (not shown) in the target database for the purpose of this example. Such an action generates a synchronization document and the synchronization document tracks the current signature or target state of all files in each of these libraries using an entry corresponding to all of the files, Update target state when changing. Using this example, the synchronization document tracks the current target state of LIBRARY_X and LIBRARY_Y, and if neither file is in the current target state, then a task is created and allocated by the platform to make LIBRARY_X and LIBRARY_Y correct Same) target state. In this example, the target state is determined by the last and hypothetical current state, and the document of LIBRARY_Y is the most current file version, so the job is assigned to AGENT X to update the files of LIBRARY_X to the same state as the files of LIBRARY_Y do. The system then initiates a session that includes the appropriate entities (e.g., peer agent (s), remote storage, etc.) and allows the necessary information to be recovered to exchange data and synchronize the library.

Another example associated with file synchronization between agents is shown in FIG. 5, which is an example block diagram related to file synchronization between the platform and the agent in an embodiment. Such an example includes three agents (A 502, B 504, and C 506) and each agent has a corresponding library (LIB_A 508, LIB B 510, and LIB C 512), but is not limited thereto. The platform allows for synchronization of these three libraries, including a single object 514 in the target database. The platform includes a library database containing a plurality of records 516, each of which corresponds to a single file managed by the platform. Each record contains information in the form of an entry for each case of the file, such entry containing information of the library including the file and the hash of the file path (P).

For the purposes of this example, report a hash (e.g., H2) other than Agent B and C (e.g., H) for a particular file. The platform reports from the information in the library database that agent A reports different hash information for files other than the files of agents B and C and that the file of agent A is the most recent version of the file. In response, the platform generates a job for agents B 518 and C 520 (e.g., WORK_B and WORK_C) to update these files to the most recent version owned by agent A and sends these files to agent A To the latest version owned by the user. The generated tasks are to find the corresponding files, fetch them, and update their files using the recovered information, which are put into the task database of the platform by the platform. The work task generated by the platform of one embodiment includes, but is not limited to, information of the location (e.g., Agent A) in the system where the most recent version of the file is stored. The work task includes information for p petating a corresponding file from an appropriate location (e.g., one or more agents that control the file's blob) and updates the files using the recovered information. The work task is located within the work database of the platform by the platform.

In such an example, agents B and C recover their respective jobs (e.g., WORK_B and WORK_C, respectively) from the platform's operations database. Upon completion of the task, each of the agents A, B, and C contains the most recent version of the file, as indicated by the hash (H2) in the library of agents A, B, and C (not shown). Also, agents B and C each report the completion of the task to the platform.

More particularly, Figure 6 is an exemplary flow chart associated with an agent, platform, and database in an embodiment. In this embodiment, the new agent A is registered (602) with the platform and an entry is created in the agent database corresponding to the new agent A. A platform responding to agent A added to the agent database creates a task database WORK_A for the new agent A (604). The task database WORK_A is generated to include tasks or tasks for the corresponding agent A. [ In addition, a new library entry is added to the library database corresponding to the new agent A, and in response, a new database (LIB_LA, 608) is created for the library information of agent A. [ In addition, a new synchronization objective (SYNC (LA), 610) is generated and added to the target database, and the new synchronization objective includes information that, by such information, To synchronize among other agent's files.

In response to the registration of the new agent A, the platform first requests the content information of the library A and then requests information on the content change of the library A. [ FIG. 7 is an exemplary flowchart related to the use of a synchronization goal (sync goal) to scan and synchronize libraries in an embodiment. Following registration processing 702 of Agent A, the synchronization target SYNC (LA) operates to generate a task and add 704 to the task database (WORK_A) of Agent A. Agent A responds to the work task by scanning all the contents of Library A to determine or know the original contents of the library, as described in detail herein. Library A In addition to passing metadata of all content to the platform, the contents of Library A are used afterwards to determine when changes to the contents of Library A occur.

Using the information in library A content, agent A monitors the library A to see if there has been any change in content. Such changes may include adding new files, deleting one file, changing the contents of some file, naming the file again, and so on. In addition to detecting a change to the contents of library A, agent A posts change 706 into change 706 into library database LIB_LA. Further, the agent A sends metadata corresponding to the content change of the library A to the platform to the platform.

The platform of one embodiment includes a synchronization database. The platform generates the synchronization database and includes and maintains a record of the agent and file status, and in particular includes an entry for each file and / or each agent that contains a content hash corresponding to the file and / or agent . When the platform detects the posting of a change in the database library LIB_LA, the platform updates 708 the synchronization database to reflect such changes in library A. This change to library A means that other libraries (e.g., B and C) are no longer synchronized with library A. As a result, the platform causes the operation of the agent 710 of the other library to occur to update the library to be synchronized with the contents of the library A. [ Thus, in this embodiment, a work task is generated for agents B and C to cause their libraries to be synchronized.

In another embodiment, instead of storing all the data in the network storage device, the platform and the agent in one embodiment require that the data be transferred to the storage device at this time. So, the platform and the agent can be used to generate the virtual NAS using the index of the metadata and the corresponding metadata of the platform. In this way, the NAS is formed using a collection of computing devices forming a grid, and thus is on site and controlled by its own agency.

In one embodiment, a small office environment includes Network-Attached Storage (NAS) for use in backing up all of the computers in an office. However, after a period of time, the data on the office computer consumes all of the memory of the NAS device and an additional storage device is needed to back up the computers on the network. Using conventional techniques, it would be necessary for the first NAS to be replaced by a NAS with a larger memory, or each computer in the office would need to be assigned to the NAS and thus not all computers would be backed up on the same NAS . However, the use of the platform of one embodiment eliminates this problem because the platform is used to communicate with an agent hosted on each of the memory devices or, alternatively, an agent hosted on each of the computers in the office, Respectively. In doing so, the platform communicates with all the members of the grid formed through the agent, and with such communication, the platform has information about all the data locations of the office. Using the metadata of the office data, the platform may be instructed by the agent for the location where the agent stores the backup data, or for the location to retrieve or read the data required by the agent to complete the processing operation can do.

As another exemplary application related to one embodiment of the platform, a user places a digital picture in a folder and subsequently uses twitter application to tweet all the pictures contained in the folder. In one embodiment, an agent is installed in one Twitter API, and the platform includes the purpose that all the pictures located in the folder are provided to the tweeter. Using this same purpose, the platform may direct such agent to provide a picture to a twitter, and then the twitter agent may be instructed to generate a tweet using the port. As another example, the twitter agent may be instructed by the platform to store all tweets received in an account at a particular location in the NAS.

In yet another embodiment, the platform of one embodiment provides content transcoding and streaming instead of file delivery. In such a case, a relatively large file to be downloaded to one device may be transcoded and streamed from the one or more peer agents to the device instead of downloading the complete file to the device.

In order to protect sensitive data, the platform of an embodiment may be configured to provide visibility, analysis, management and security for business content across mobile devices, desktops and public, private or local clouds, as described in the detailed description herein Software-as-a-service (SaaS) -based data synchronization and content management platform. The platform includes a cloud-based, distributed data system that can locate, track, and manage content across devices, users, and geographic distribution. The platform is configured to combine the strength of a peer-to-peer (P2P) system with the centralization and control of a more typical cloud data storage platform. This new hybrid approach brings decisive control and security.

The platform of one embodiment may be a cloud-based policy engine of the platform, an agnostic file storage environment, high efficiency data transmission, automated data-discovery and segmentation, and multi-layered enterprise- Based synchronization and content management platform. In traditional cloud service environments, the cloud serves as "dumb storage", while most platform intelligence is hosted on mobile and desktop clients. The platform of one embodiment takes a more flexible, robust and secure approach. Instead of a "smart client" accessing "bonus storage ", the platform has a" smart cloud " With this approach, the platform generates commands to clients (mobile and desktop devices) and improves functionality and security.

8 is a block diagram of a platform including a policy database and a rules engine in an embodiment. The platform includes all service policies at the cloud level within the policy database, and the policy database is linked to the platform rule envi- ronment. For example, the policy may be "Copy a new file in folder X to a device of users A, B, and C ". In addition to the policy of the policy database, the platform maintains a complete database of file metadata, users, device groups, and organizations, providing the platform with a complete understanding of the environment. The configuration of the platform is connected to receive device features, file metadata, and permissions (e.g., user permissions, group permissions, organization permissions, etc.).

At the client level, the local agent monitors (i) the event (e.g., a new file added to the folder X), (ii) performs indexing of the file (the file includes the following important terms) Upload file metadata, device state and new events to the platform, and (iv) process the operations originating from the platform (e.g., data movement, folder scanning, file creation, peer connection, etc.). The agent reports the data of each piece moving around the network to the policy engine in the cloud, activating the platform to know where the data is located and needs to be located.

When a new policy is added, or a new event occurs at the agent level, the platform acts as a director or "traffic police" to determine what action should be taken. Based on the policy engine, the platform generates commands to local agents to perform their tasks. The agent (s) merely perform the operations originating from the policy engine. This approach facilitates rapid repetition of new usage events (e.g., data backup, information governance) due to the extraction of other important components of the service that will be easily achieved and the intelligence in the cloud, .

Traditional cloud service providers allow customers to upload and store data within their cloud infrastructure as file storage access points. These providers benefit from such an architecture by combining billing customers for the repository and all user data within a single storage system, which allows service providers to deduplicate content and charge for unused repositories . Companies can not control their data because they can not choose their storage location and companies must trust their service providers to precisely eliminate redundant data, their sensitive business content and not being mixed with other users on the system This approach has many security problems, including the need to share their encryption keys with service providers in order to use features such as sharing, and even exposing data to potential gaps.

Unlike traditional cloud services, the platform of one embodiment uses a variety of public, private, and local clouds as Fangry storage access points. To deliver this aggressive file storage access point, the plot form separates the file contents from the metadata and handles the two very differently. 9 is a block diagram illustrating metadata separated from other platform configurations in an embodiment. More specifically, the metadata is centered and stored in the cloud with the server, while the actual file or file data is stored as determined by the customer on one or more storage access points. Further, by advanced data fingerprinting and hashing controlled by the platform, file data is securely stored across multiple data stores. Under this approach, customers can choose where their files are stored, which improves security, leverages existing infrastructure, enables policies to store data locally, and meets Safe Harbor requirements.

Traditional cloud service providers typically perform an inefficient two-step process for data transfer by uploading all data from the client to their centralized cloud and then downloading back to the connected client. Depending on the data deduplication level, hashing and P2P capabilities, this data transfer process is time consuming and results in significant data transfer costs.

In contrast, the platform of the embodiment uses a set of techniques for transmitting data. For example, the platform of the embodiment performs block level file transfer by moving blocks of data instead of the entire file. As an example, when a 1 GB file is modified, a hashed block of the modified file (e.g., a 10 MB block) is sent instead of the entire 1 GB file.

The platform includes a data storage index that allows data blocks to be indexed across the entire system and transmitted to the agent requesting data from the closet point. For example, if a file has already been uploaded from the one agent to the cloud, the requesting agent downloads it directly from the cloud instead of asking the original agent to re-upload the file to the cloud for downloading.

Figure 10 shows, in an embodiment, the connection type of the platform. The platform of the embodiment uses two connection types. The first connection type includes HTTP / TLS between various local configurations and online servers and services. It is equivalent to a web browser and has the same firewall behavior as a browser on the same machine. The second type of connection in the embodiment is a peer-to-peer (P2P) protocol. 11 shows, in an embodiment, a P2P connection type. The platform uses P2P communications to efficiently move data between agents. For example, two agents on the same LAN can move data directly more efficiently than they do through a cloud storage provider.

The platform of the embodiment is not limited to the P2P communication using the User Datagram Protocol ("UDP"). Using the information from the service, the agents will attempt to establish a UDP session with each other. If both agents are behind the same firewall, this is successful. For peers outside the firewall, communication becomes more complex. Some corporate firewalls will not allow such traffic, and in these cases, the platform will "relay" the data between peers via HTTP / TLS.

The platform polices its upstream bandwidth by a plurality of agents to perform interoperable file transfers that can move large files into fragments faster than a single agent can do alone. This technique is used in both, but not limited to, cloud storage relays and P2P data transfer.

The platform of the embodiment performs non-sequential / simultaneous transmission, wherein unordered data transmission is supported by simultaneous file upload and download. Using this method, when all the blocks of data arrive, the data is reassembled in the agent, regardless of the order in which they are transmitted.

The providers of conventional cloud services provide minimal data visibility within their platforms. Users can access their files, but an information technology (IT) administrator has little invisibility into the data in the system. Some service providers allow IT administrators to view listings of file names across the system, while others do not provide details on files within the system.

The exemplary platform not only provides the IT administrator with a complete listing of the organization's files in the system, but also analyzes the contents of each file to determine how sensitive or confidential each document is. To achieve this, the platform performs a two-step process, one of describing between the person and the business content, and the next determining the sensitivity of the business data identified.

To describe between the person and the business content, the agent scans the document across the local data store and extracts the key term from these documents. These key terms are then compared across the entire organization to generate a list of company specific key terms. Using organizational key terminology and other proprietary methodologies, the platform separates business and human data across local repositories, allowing IT managers to focus solely on corporate data.

To determine the sensitivity of the business data, the platform can search for the presence of a particular key term (e.g., "company secret") and analyze the specific grammar of the data (eg, credit card number, e-mail address, telephone number, etc.) And performs other proprietary analysis. This segmentation allows IT managers to identify the most sensitive content within the business. Once the sensitivity of the document becomes part of the metadata, the platform allows IT administrators to enforce specific controls over the data, limiting where and how data is accessed and shared.

Automated data-discovery and segmentation of content allows IT managers to identify sensitive business content without relying on end-user tagging or classification, find critical content without the hassle of people or non-critical business files, So that a particular control can be created to protect it.

In a conventional cloud service platform, each individual user data is stored together and deduplicated over the entire data set (e.g., all user data stored using a cloud service provider). This mixed approach can lead to potential data leakage if the file is not correctly indexed.

The exemplary platform is configured to manage data in a controlled and secure manner around a framework that provides security at the access, application, infrastructure, network, transport and data levels. This approach makes it possible for the organization to be managed in the "security silo" with data from each user to have its own set of security information as described in the description of this specification.

The platform provides each organization with a unique organizational encryption key that is used to encrypt data within the shared repository or cloud. Also, any hash computed on the data is salted with a value unique to the organization. Even if the underlying data is the same, the two organizations will not share the same hash. This prevents the platform from being deduplicated and vulnerable among customers, while enabling deduplication at the organization level, which saves storage space and minimizes unnecessary data transfers. When an unauthorized user accesses an end-user service or data store, the user will be limited to viewing only unencrypted blocks.

The platform is configured to enable file sharing among authorized users. All authorized agents and clients can uniformly access and contribute to the organization's data. Data is not encrypted at the user level, so the data belongs to the organization. When a new user is added to the organization, the new user receives the keys required to create and access data for that organization, allowing them to interact with other users. The data generated by the user is available to other users in the organization even after the user leaves the company.

Once an account is provided and encrypted using a password from the organization's IT administrator and user, the organization's encryption key is generated by the platform. The key can not be accessed without the user or administrator's password, which is never stored by the platform. If the user is in an active session, does not have his or her provided credentials, and the master key is not present, then the platform is unable to decrypt the customer data. However, the platform does not store a recovery key, which, if lost, can be used to apply a new password to the account.

Device level data is stored on its local file system, and the platform does not encrypt or encode local device file system data, but is not limited thereto. However, any data or metadata that leaves the device may be encrypted using SSL (from device to device), end-to-end encryption (from device to device), or dotless encryption (from device to cloud or shared storage) do

Each agent on the device has two 2048-bit RSA public / private key pairs in one embodiment. One used to secure end-to-end encryption, the other used to sign messages and validate the message source. These keys are pre-generated and assigned by the platform, but once they are assigned, they are not stored in the cloud. Keys and certificates are always stored in the secure key store provided by the operating system. Unlike conventional P2P, there is no "anonymous peers" in the platform, because each and every connection between agents occurs because the central cloud is determined to be the most efficient of these. The entities of the source and destination of the data transfer are known prior to connection and are independently verified by all agents. Agents can not allow connections they do not anticipate.

When agents are combined or connected together to exchange data, they use public key cryptography to provide end-to-end cryptography of all data transmitted between them. The platform has public keys for all agents and provides them with two ends of arbitrary P2P requests. The platform does not have a private key, which is only at the agent level, but the present embodiment is not limited thereto. The agent uses these private keys to securely establish a symmetric encryption key that is used to encrypt data between peers using a government-grade AES-256 algorithm. This ensures that an unauthorized user can not interpret the contents of the message sent between peers. Sessions between agents are transient, and when they expire, a new connection is established, which requires a new key to be exchanged.

SSL is a widely accepted standard for secure communication from and to Web servers. Whenever a client or browser connects to the platform, it uses SSL to secure traffic. Metadata and agent commands are also secured in this way.

The platform ensures that all data is at-rest and encrypted in the cloud or shared storage. When agents are required to store data, they encrypt the data using an organization cryptographic key. Only authorized agents can decrypt the stored data in this way. At-the-rest data is also encrypted using the AES-256 algorithm.

Separation of data and metadata in the embodiment provides additional security and complete control while minimizing cost. All data is hashed and encrypted with the key unique to that customer, and the metadata is stored separately from the data.

The platform provides an easy way to access, update and share critical business data across mobile devices, desktops and the Web. Users can access files across iOS and Android smartphones and tablets, Windows and Apple computers and web browsers. Files modified on the device are automatically synchronized to all other authorized and connected devices. Users can also share files with recipients or individuals external to the organization via two-way shared folders or one-way web links.

More specifically, the platform of the embodiment provides backup and recovery to protect data, applications and operating systems across various environments (e.g., desktops, mobile devices, servers, cloud services, etc.). It allows users to monitor installed backup applications, consolidate key backup metrics into managed code, and alert users that sensitive files are at risk.

The platform ensures that all sensitive documents are included in the backup plan and ensures that these documents are currently backed up. If any sensitive documents are not protected within a time period, the administrator changes and locates sensitive documents across the organization. The platform also stores from an alternative location if the backup fails, and ensures that sensitive documents are backed up in multiple locations or duplicate backup locations due to user redundancy. Backups of files are deleted according to certain retention policies, and sensitive documents are backed up to a more secure storage location offsite. In addition, the platform provides a backup service that allows deployment of remote configuration and backup operations.

Backup and recovery provided by the platform includes file source backup of desktops, servers, shared storage, mobile devices and several online repositories. File types associated with backup and recovery operations include data files (e.g., documents, video, music, images, etc.) and application specific files (e.g., Outlook, PST, MS Exchange, databases, etc.). The file selection selects files to be backed up based on the file type and / or folder location, or alternatively performs backup of the entire device or computer system (e.g., system image). The file store stores external hard drives, NAS or online selected files, or selects multiple locations for redundancy. Every time a storage device is deleted, and whenever a schedule is backed up based on a schedule, an automated or scheduled backup automatically adds new or changed files to the backup.

The file recovery of the embodiment is configured to easily store the selected file and is configured to completely store all the files if the computer is malfunctioning or the file is accidentally deleted. Data loss prevention prevents data loss by monitoring data during use (e.g., endpoint action), during motion (e.g., network traffic), and during at-rest (e.g., data storage). File-level DLP software identifies sensitive files, and then embeds information security policies within the files. On a platform always, where my access provides online access to all files and folders through the user console. The version history stores the previous version of the file so that the user can revert to these versions. The deleted file is stored during a period of time so that if the deletion is accidental, the user can restore the deleted file. File systems and unstructured content are achieved based on company policy, thus reducing costs and mitigating risk.

The exemplary platform provides file sharing and access, which allows a user to access and share files and other content across a variety of environments (e.g., computers, mobile devices, servers, cloud services, etc.) and the web. The files can be shared via two-way folder sharing and web link sharing, and key metrics and control can be integrated into the management console.

The platform restricts or controls sensitive documents by preventing sharing with a particular user, group or outside of the company. Sensitive documents can not be accessed and / or downloaded to the mobile device through the platform, but rather can be viewed online to maintain control, and document downloads are limited to temporary copying and are removed if they are not connected. The file can not be copied to an external or external storage device or location in the platform-related folder. In addition, the file can not be sent as an attachment as an email, as a text electronic messaging, nor as a file uploaded to social media. The embodiment includes an exception process that allows a single request. With access to the document, detailed reporting of the location of the document accessing the modifications and history is also possible.

The file sharing and access of the embodiment's platform provides content management for creating, managing, editing and storing files across devices and systems. The synchronization of an embodiment selects a file to be synchronized across the device in order to make it available from any device. Also, changes are automatically synchronized. Anytime, anywhere access allows access to arbitrary files from any device (e.g., desktop, laptop, phone, tablet, online, etc.). Shared folders give access to folders that can be viewed internally and sometimes by external users, edit files contained within folders, and make changes that are synchronized to all users. Including but not limited to, allowing more granules (eg, managers, editors, viewers, etc.).

The platform includes a public link whereby the file can be shared over a link that can not be accessed by any user. The file is read-only to prevent editing, but the user can view the file, and downloading is sometimes restricted. External document management and security controls what happens to files after they are shared externally by locking them so they can not be printed or edited. Joint audits provide a comprehensive auditing and tracking tool to give better viewing and file downloading activity for content sharing. The user can know who did not download the related file. Bulk file transfer is an alternative method of email for transferring bulk files online, such as sharing public links. Email integration allows a user to email any file directly from any device by right-clicking on the file or selecting an email option. The mobile preview allows the user to view any file on any mobile device. Editing mobile documents provides the ability to edit files on a mobile device. Mobile printing allows a user to print any file on any mobile device by specifying a default remote printer. Mobile scanning allows a user to scan an image or paper document from a mobile device for access across the device. The quarantine system uses antivirus capabilities to isolate infected files from the hosting system. Regulatory compliance takes steps to comply with SOX, HIPPA, PII, PCI, FINRA, FDIC, SAS70, Basel II, Dodd-Frank and FCPA.

The platform of the embodiment provides collaboration that includes concurrent editing (e.g., word processing, spreadsheet, presentation, project plan, etc.) of documents across a variety of environments (e.g., desktops, mobile devices, servers, do. The file in use alerts you about the shared document, notifies you about the modified document, and allows modification and access history. Thus, the platform provides a notification to the user if the document is in use and prevents conflict, Locks the user, sends an alert when someone edits or adds a shared folder or file, and notifies the user of the published document. The platform allows online collaboration only through concurrent editing, and provides reconciliation and merger tools, revision and access history, check-in / check-out systems and office consolidation.

Collaboration of embodiments provides many important features. Multiple people can view and edit the same file. Grant granite sharing rights to multiple people (e.g., managers, editors, viewers) to edit the same file. Collaborative audits provide a comprehensive auditing and tracking tool, giving a better view of content sharing and file download activity. The user can know who has not downloaded the related file. The activity history keeps track of all file activity, such as when and by whom file changes were made. When someone edits or adds content to a shared folder or file, the email notification sends a warning. Comments can comment on files and / or discussion areas to add feedback or discuss changes. For collaboration and discussion, an annotation adds a note to an existing file. Business process management provides the automation of business processes through the use of information technology, more efficient, effective and changeable. This includes items such as workflow or task management.

Job flow / task management assigns tasks and deadlines as part of the review process, and assigns file-specific tasks to request updates, reviews or approvals. Project management breaks the target into milestones with individual deadlines, moves towards the final goal, and assigns tasks based on the various milestones. Online document editing does not download them first to the user's local computer, but to various file types online. Editing a mobile document edits a file on a mobile device. Mobile preview provides the ability to view any file on any mobile device. Mobile printing prints any file on any mobile device by designating a default remote printer. Mobile scanning scans an image or paper document from a mobile device to access across the device. Continuously digitize paper documents.

The platform of the embodiment provides document management, which controls access to documents based on user privileges, document availability, and document status. The embodiment document management is integrated with a third party application (e.g., Office) to maintain workflow, activate versioning and auditing trails for documents, and enhance security requirements for documents. Thus, the platform can grant limited rights management that allows users to index, track and catalog business files, classify file sensitivity, and provide file access to individuals or groups.

The platform assigns rights to files to users (e.g., administrators, editors, viewers) and limits sensitive documents in many ways. The file can not be modified and is read-only for a particular user, and if there are no other requests, it will be destroyed after a period of time and can not be captured by the image capturing software. The file format is switched (e.g., to PDF, etc.) before being distributed (e.g., read-only) so that the contents of the document can not be copied and pasted into another document. In addition, the file can only be stored on the company server, so it can not be stored on the public cloud, and file and file derivatives are tracked over the storage device (s). In addition, the platform includes files and non-files based on content (e.g., Wikis, Evernote, social media, etc.), and there is an exception process to allow requests once. The platform provides detailed reporting of the location of the document, who accessed the document, who actually viewed the document, what device and where it looked. Modification and access history is also available through the platform.

The platform discovers confidential stored data using identifying business information. The platform extracts the keywords and compares the extracted terms across the organization. The platform identifies business documents across multiple sources, for example, using one or more document names, document size, proximity (assuming 100% of the documents in the folder are 100% business), keyword comparison and hash comparison can do.

The platform also categorizes sensitive data. The displayed document is manually tagged as sensitive. Examples of selected key terms include "Company Confidential "," Income Statement ", "Partner Pipeline "," Password " The learned key term is the most relevant key term in the document marked as "confidential". Platforms infer based on the detected content (eg, five examples of company names, etc.). In addition, the platform may be implemented using grammar (e.g., "### - ## - ####", "3767 - ###### - #####", aaaaaaaa@aaa.com, Quot; ### - #### "). The platform records document characteristics such as who is the owner, where the files are, what permissions are, and who accessed them.

The platform also categorizes sensitive data, including intellectual property rights, customer information, employee information, sales information, marketing information, and financial information, such as intellectual property rights, including proprietary engineering design, scientific formulas, source code, trade secrets, Unrecognized) product information. Customer information includes name, email address, customer password, phone number, social security number, address, credit card number (last 4 digits) and date of birth. Employee information includes Social Security number, date of birth, and address. Sales and marketing information includes customer lists, quotes, marketing and sales plans, material costs and profit margins, and project plans and consumption plans. Financial information includes financial records and strategic business plans.

Document management included within the platform includes search / trace indexing and includes searching for and recovering an electronic document through a unique document identifier, indexing the metadata, or through a word index extracted from the contents of the document. Rights management allows an administrator to grant access to a document based on the type of person of a particular person or group.

The collaboration provided by the platform of the embodiment can be restored, modified or edited by the authorized user. Multiple users can view and modify documents simultaneously in a collaboration session, and during a collaboration session, the platform stores the markup done by each individual user. However, while the document is modified or edited by the user, access to other users should be blocked. In addition, the platform sends alerts and notifications about document availability, but is not limited thereto.

The embodiment's versioning restores the previous version of the document and allows the user to continue working from the selected point. Third-party integration can integrate with third-party applications, allowing users to recover existing documents from the document management system repository, and to save modified documents back to the repository in a new version, I do not leave. The disclosure and distribution of documents through the platform includes remediation, peer or public review, authorization, printing and approval. Security includes compliance requirements for a particular document, depending on the type of document (eg SOX, HIPPA, PII, PCI, FINRA, FDIC, SAS70, Basel II, Dodd-Frank, FCPA etc.) can do. The platform includes granular capabilities such as printing, copying and forwarding, as well as watermarking and wiping capabilities in documents. Workflows are combined with connection management features such as providing automatic routing of individual documents or managing scheduling, checklists, and review notes. External branch management and security controls how files are shared and integrates with other modules or third party systems.

The exemplary platform provides data intelligence and information governance, which can include data (e.g., documents, Evernote, Wikis, etc.) across desktops, mobile services, local storage, networked storage and cloud services . These data intelligence and information governance create more informed decisions about the propensity of management, retention and business data, identify compliance violations, and make infrastructure planning decisions. The platform determines the usage analysis of location, owner and business dates and includes limited information governance (eg, SS number, credit card, etc.) as well as limited information compliance (record retention, etc.).

The platform allows the user to determine the location of all sensitive files and to understand specific information about the data. In addition, a user may remove files from any unsecured location (e.g., mobile device, public cloud, home computer). The selection policy may be applied to file metadata (e.g., retention, due date, access, etc.) for record retention, defendable deletion and compliance enforcement. Full document retrieval can be performed across all data sources through file name, document key term, or full document retrieval.

The data intelligence and information governance of the platform is based on how much data belongs to the user, where the data is located, who owns the data, where the data is, the age of the data, Includes decision-level maps and business analysis or rules. The platform is hosted by providing file classifications, retrieving content, discovering compliance and rule violations, revealing age, and gaining visibility across content that is non-business related. Information genealogy provides a set of security-related chronological sets of records, and a destination and source of records that provide a sequence of activities. The platform keeps track of all file relationships and where they are, and information governance provides policy management, including record retention, defensible deletion and rule enforcement, and provides policy management, including account number, social security number, credit card number, Records, strategic business, business and critical information assets such as flat and IP / source code. Once exposed sensitive data is identified, the automated policy modifies the security attributes of the file, moves the data to a more secure system within the enterprise, or deletes the risky item.

Records management implemented by the platform implements and automates a leading and persistent record retention and propensity strategy. The file sharing cleanup allows the user to gain control of the business data sprawl by understanding the user's environment. The platform classifies the data, updates the data attributes, and assigns permissions. Intelligent e-Discovery provides legal hold notification, true early case assessment and intelligent collection. Data erasure and cleanup of the platform uses data topology maps and classifications to identify non-business data and to perform preventive data cleanup prior to commencing information management such as storage / data movement, e-discovery, records management or compliance obligation . Storage optimization optimizes the use of existing storage resources, reduces storage costs, monitors with data topology maps and classifications, and plans for future storage needs.

The platform of the embodiment provides mobile device management, which monitors and supports mobile devices to enforce policies by activating an organization, as well as controlling data to maintain a desired level of IT control across a plurality of platforms and applications Protect. The platform provides end-to-end security through centralized management of mobile devices through a single mobile device software product. The platform also includes device asset tracking, device application tracking such as GPS asset tracking, password compliance / SSO, remote locking / wiping, tracking apps and data being uploaded, viewed and edited.

The platform allows the user to perform remote wiping across all sources, removing the original files and their derivatives, remote locking, and detecting and protecting jail-broken devices. Password compliance with single sign-on and device configuration, and monitoring for network, e-mail configuration and battery life. Application management limits applications, pushes mandatory applications, limits application monitoring (eg, uploaded, viewed data, etc.) and ensures that all applications are up to date and functioning properly. The platform also includes GPS tracking and reporting / real-time notification of non-compliant devices.

The mobile device management of the embodiment includes mobile risk management that provides real-time visibility to all mobile devices connected to the associated resource, and includes between embracing employee selection (e.g., bring your own device) and protecting corporate data . Mobile security provides antivirus technology, advanced firewall and anti-spam features. GPS asset tracking locates and tracks the coordinates of mobile devices within the central console. Remote locking / wiping protects your data in the case of your device and unauthorized access. The platform's device list tracking provides administrators greater visibility through the ability to track files and data uploaded, viewed, and edited on the device and to categorize files (via classification, recent viewing / editing, etc.) do.

The device application management of the platform distributes the applications based on group settings, restricts or allows the specified public market apps, and pushes the mandatory applications. In addition, the platform can not warn and access non-compliant devices, manage proprietary applications, and deliver them to users without exposing them to the public application store. The platform also enforces updates to the device. The security policy management of the embodiment includes push proofs, email server settings, restrictions, and camera settings (e.g., Android devices, iOS devices, etc.) for devices. The platform lists process execution, installed applications, battery life and network information. The user can get a real-time notification and warn the management about the exception.

The platform creates a user report by completing an audit report of user activity (e.g., file upload, file download, application usage, activity sharing, etc.). The platform is configured to manage mobile content by pushing corporate documents and sensitive files to a mobile device in a secure manner while preventing data loss, transferring remote updates to a file, and removing content without end user intervention. Instant recovery and backup provides the ability to restore all files to the device at once, if the file is lost or corrupted. The platform can remotely erase the device, provide policies and applications to the device, a black or white list application, and detect and protect devices that have jailbroken.

The platform of the embodiment provides resource usage and security, which integrates information related to the situation and provides visibility to various environments (e.g., mobile devices, desktops, servers, etc.) to monitor, optimize and protect data, applications and devices do. The platform includes hardware, software and application usage, resource consumption for storage, application information tracking and storage for RAM and network monitoring, data cleanup and archive optimization.

The data deletion and cleanup of the embodiment uses a data topology map and classification to identify non-business data. The platform performs a defensible data cleanup prior to initiating information management such as storage / data movement, e-discovery, records management, or compliance obligations, and also maintains stale data that needs to be maintained. Storage optimization optimizes the use of existing storage resources, reduces storage costs (eg, data deduplication), and also uses data topology maps and classifications to monitor, plan for future storage needs, and consume resources (Eg, storage, RAM, network monitoring).

Platform resource use and security include applications and information tracking that pinpoint how hardware, software, and applications are used. Users can track the most used programs, websites and file types. Resource consumption reports indicate how much RAM, bandwidth, and storage space the user is using. Context-aware software for optimization tracks and builds patterns of utilization across time, reducing unpredictability by increasing visibility through application usage and data movement. The platform redirects valuable resources to key users, applications and / or programs. Improved visibility allows for planned and real time assignments.

Platform client security provides antivirus technology, advanced firewalls and anti-malware. Platform activity security monitors and alerts administrators of abnormal behavior to devices and / or clients. The platform's cloud security includes policies, technologies, and controls to protect data and applications in the cloud. Deployment and imaging deploys and manages computers from a central location. Android code signing manages applications for authorization keys and easy application version updates on Google Play. The device configuration management distributes the application / software based on the group settings, restricts or permits the specified application / software, and pushes the mandatory program. The platform alerts and disables access to non-compliant devices. The platform manages proprietary applications / software, delivers them to the user without external exposure, and also enforces updates to the device. Endpoint security ensures the operating system, web browser, and other applications are up-to-date before allowing access.

The exemplary platform includes a management console that gives IT managers control over and control over how business data is accessed, viewed, modified, and shared. Figure 12 shows an exemplary screen of a management console in an embodiment. The online management console provides real-time visibility into every aspect of the service, including how users are activated, what devices they have connected to the service, what files they want to synchronize, and who they share data with. In addition, the management console allows IT administrators to proactively manage critical features of services, including user permissions, file access restrictions, shared control, and remote data deletion.

The management console includes the ability to control various aspects of the file synchronization process. Because the platform automatically identifies sensitive documents, IT managers can restrict important business documents from being synchronized across services or shared internally or externally. In addition, the IT manager can set the maximum size and bandwidth consumption for files that can be synchronized with the control repository, or can specify which file classification (e.g., music and video) is prevented from being on the network. The IT administrator can also define whether the file can be accessed or downloaded from the user web portal. Figure 13 shows, in an embodiment, an exemplary embodiment that includes file synchronization control.

The platform delivers real-time, automated activity monitoring, auditing, and reporting to IT managers, detailing important system activities by date, time, user, device, file, and other factors. To enforce security policies, IT administrators can view unrecognized logins, password reset attempts, and the number of sensitive files that share events and other activities. Figure 14 illustrates an exemplary screen including security activation monitoring and notification in an embodiment. In this example, IT administrators are warned of potential security issues, because five unrecognized login attempts to an IT administrator's account are made at locations unknown to Cluj, Romania. When a security event occurs within the system, the IT administrator can receive an alert notification, for example, via a management console, IOS / Android app, text or email.

FIG. 15 illustrates an exemplary screen including a document audit trail in an embodiment. The platform records the complete file history of the document in the service. For each document, the IT administrator can see when the file is added, modified or deleted. In addition, an IT manager can determine which devices are accessed and which devices are geographically located. This functionality is essential for shared documents that are modified by multiple users across multiple devices. In addition to editing the document audit trail, the complete revision history of each file is also stored if the IT administrator or user wants to revert to a previous version of the file.

Figure 16 shows an exemplary screen, including an example of a file search and classification, in an embodiment. Using automatic data discovery and segmentation capabilities, IT managers can identify sensitive business files based on deep content searches and key term extraction. The IT administrator can then search for and view specific documents, including owner information (e.g., customer, employee and financial information), as well as set specific restrictions to control this information. In addition to closely managing sensitive documents, IT administrators can search for files across an organization by file name. IT administrators can view the entire file synchronized across the organization, understanding file type breakdown (document, music, video, etc.) or distribution of files based on size. This information can help IT administrator users to add human content to the service or to misuse the solution.

The platform can determine which users can share documents within an organization by setting up shared folders with specific collaborators. Unauthorized users can not have the ability to access shared folders without the permission of the IT administrator or trusted user. IT managers can also control which users share through a one-way web link. Also, for both Web links and shared folders, IT administrators have a complete history of all sharing activities (adding, modifying, or deleting files by users, devices, locations, etc.). Figure 17 shows an exemplary screen, including an example of controlled user sharing, in an embodiment.

Figure 18 illustrates, in an embodiment, an exemplary screen including remote device management and geolocation services. IT administrators can remotely manage mobile devices and desktops through the management console. For example, when an employee is terminated in an organization, the IT administrator can remotely remove the user from any sharing activity, unlink the device from the user's account, and stop the service to the device. IT administrators can remotely wipe specific devices and immediately remove sensitive business content. The platform can integrate geolocation services into the management console to identify specific locations for system events and to monitor the location of mobile devices and computers. This is particularly useful if an IT manager wants to limit business content from home computers and other personal devices.

The platform allows IT managers to choose where to store their core business files. An IT administrator can choose to store files in the Memeo data center with another cloud storage provider (such as HP or Amazon) or an in-house installation in a server or NAS environment (such as NETGEAR). Figure 19 illustrates an exemplary screen that includes, in an embodiment, selection of a storage location. The flexible storage model improves security for customers by allowing customers to store files locally or with a cloud provider they have already experienced. This approach also enables IT managers to use existing storage infrastructures that reduce operational costs.

The embodiments described herein include a system including a platform including a processor coupled to a plurality of databases. The system includes a grid comprising a plurality of agents coupled to the platform. Each agent of a plurality of agents is an agent of the platform running on the client device. The system includes metadata of the contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents. Each agent of each client device generates metadata and provides it to the platform. The platform includes metadata in place of content, uses metadata to determine the location of the content, creates a target representing the task to maintain the state of the content, creates a plurality of tasks corresponding to the target, To the agent accessing the content corresponding to the task. Each task is a processing task for the content accessible by the agent guided by the platform to be performed by the agent.

The embodiments described herein include a platform including a processor coupled to a plurality of data; A grid comprising a plurality of agents coupled to the platform, each agent of the plurality of agents being an agent of a platform running on the client device; And metadata of the contents of a memory accessible by a plurality of client devices corresponding to the plurality of agents, each agent of each client device generating and providing metadata to the platform, wherein the platform includes metadata instead of content , The metadata is used to determine the location of the content, the goal to represent the task to maintain the state of the content, the plurality of tasks corresponding to the goal, and each task to access the content corresponding to the task To the agent. Wherein each task is a processing task for content accessible by an agent guided by a platform to be performed by an agent.

The platform of the embodiment is a master controller for a plurality of agents, wherein the plurality of agents interact with the platform as controlled by a plurality of tasks.

Each agent of the plurality of agents of the embodiment functions independently of the platform and the other agents of the plurality of agents.

The platform of the embodiment receives content metadata instead of receiving content, wherein a plurality of client devices hosting a plurality of agents comprises a distribution storage device containing the content.

The platform of the embodiment uses metadata to maintain a master index of the contents of a plurality of agents in a plurality of databases.

The metadata of the embodiment includes data on the location of the content.

The metadata of the embodiment includes data on the status of the content.

The metadata of the embodiment includes data for the entities of a plurality of agents.

The metadata of the embodiment includes data about contents that each agent accesses.

The metadata of the embodiment includes information of a plurality of tasks performed by a plurality of agents.

The task of the embodiment involves tracking the location of the content over the grid.

The tasks of the embodiment relate to managing the storage of the content in the grid.

The tasks of the embodiment relate to managing movement of the content in the grid.

The tasks of the embodiment involve processing the content in a grid.

Each of the tasks of the embodiment includes a condition of completion for the task.

The plurality of agents in the embodiment collectively monitor the contents as indicated by the platform.

The plurality of agents in the embodiment collectively store the contents as indicated by the platform.

The plurality of agents in the embodiment collectively transmit the contents as indicated by the platform.

The plurality of agents in the embodiment collectively perform the processing operations on the contents as perceived by the platform.

Each agent in each client device in the embodiment indexes the contents of memory accessible by the client device.

The plurality of databases of the embodiment includes an agent usable on the platform and an agent database containing information of each agent.

Each agent in an embodiment includes at least one library, wherein the library represents an apparatus having an access at least including read access and write access.

The plurality of databases of the embodiment includes a library database including a list of libraries corresponding to a plurality of agents, wherein each library of the grid is separately shown in the library database.

Each agent in the embodiment accesses each library corresponding to the agent.

The plurality of databases of the embodiment includes a target database containing a list of targets, each target of the list of targets being created by the platform and corresponding to at least one library, the target being used do.

The list of goals of the embodiment includes a collection of libraries on which tasks are to be performed.

Each goal in the embodiment corresponds to at least one library and is used by the agent to execute at least one task on the contents of the library.

The platform of the embodiment uses a target to read a plurality of libraries of a plurality of agents.

The platform of the embodiment uses a target to identify at least one of a discrepancy and a difference in content accessible by a plurality of agents.

The platform of the embodiment uses the target to create at least one task to remove at least one of the discrepancies and differences identified in the content.

The plurality of databases of the embodiment includes a task database.

The platform of the embodiment creates a task database corresponding to each agent, and the task database includes tasks to be performed by the agent.

The task database of the embodiment includes a description of each task to be performed by the agent and information necessary for the agent to perform the task.

The plurality of databases of the embodiment includes a capability database that includes information about capabilities of a plurality of agents.

The plurality of databases of the embodiment includes a synchronization database that includes and maintains a record of a plurality of agents.

The synchronization database of the embodiment includes a record of the file status of the contents of a plurality of agents.

The synchronization database of the embodiment includes an entry for each file, the entry including a content hash corresponding to the file, the content hash including a hash of the list of blobs representing the contents of the file, Each blob of the file contains a representation of the fragment of the file in the content, and the fragment is the organization of the file.

The synchronization database of the embodiment includes an entry for each agent, the entry including a content hash corresponding to the file of the agent, the content hash comprising a hash of the list of blobs representing the contents of the file, Each of the blobs in the list contains a representation of a fragment of the file within the content, and the fragment is the organization of the file.

The platform of the embodiment uses a plurality of agents to control the transfer of content among the client devices.

The platform of the embodiment controls the synchronization of content among the client devices using a plurality of agents, the synchronization of which includes synchronizing the content in response to a change in content.

The transmission of the contents of the embodiment includes block-level, non-sequential transmission of content.

The transfer of the contents of an embodiment includes transferring a first block of content from a second client device to a first client device and transferring a second block of content from a third client device to the first client device.

The plurality of tasks of the embodiment include scan tasks.

The scan task of the embodiment includes an agent that regressively monitors the library corresponding to the agent and reports any changes from the library to the platform.

The reporting of embodiments includes locating the files of the library that contain changes in the local database of the client device hosting the agent and providing metadata of the local database to the platform.

The plurality of tasks of the embodiment include the described tasks.

Describing an embodiment includes an agent that copies at least one blob of a file from a first location to a second location, wherein each of the first location and the second location corresponds to client devices associated with the grid.

At least one blob of an embodiment includes an indication of a fragment of the file in the content, wherein the fragment is a configuration of the file.

The described tasks of the embodiment include the conditions of completion.

The conditions of completion of the embodiment include at least one of restoring the blob corresponding to the written task and identifying the blob to be duplicated during the written task corresponding to the correct file.

The plurality of tasks of the embodiment include an upload task that includes copying an indication of content from a device accessible by the agent to a remote storage device.

The agent of the embodiment reports to the platform what to add to the content accessible by the agent of the file, and in response, the platform assigns the task to the agent to upload the file.

In response to the task, the agent of the embodiment determines if the file is present in the remote storage device and, if it is determined that the file does not exist, uploads an indication of the file to the remote storage device.

The upload task of the embodiment includes an agent that copies at least one blob of the file from the device accessible by the agent to the remote storage device.

At least one blob of an embodiment includes an indication of a fragment of the file, wherein the fragment is a configuration of the file.

The plurality of tasks of the embodiment include delete tasks.

A task of an embodiment includes a plurality of states including one of waiting, pending, and completed, wherein the platform tracks the state of each task of the plurality of tasks.

Each agent in the embodiment maintains locally in the client device task assigned to the agent.

The agent of the embodiment periodically polls the platform to identify assigned tasks.

The agent of the embodiment is required to complete the task and includes a hierarchy for locating task information located at the remote device.

The layer of embodiments includes an agent that retrieves a local database of client devices hosting the agent.

The layer of the embodiment includes an agent that communicates with at least one peer agent of the plurality of agents to find task information.

The agent of the embodiment includes the entity of the peer agent that owns the task information.

The layer of embodiments includes an agent for recovering task information from a remote storage device.

The agent of the embodiment retrieves the entity of the peer agent in the ordered list from the platform and retrieves the task information according to the ordered list.

Each agent in the embodiment includes a plurality of configurations that execute in parallel.

The plurality of configurations of embodiments include a provider configuration for recovering a task designated for the agent from the platform and storing the recovered task in a task database local to the client device hosting the agent.

The plurality of configurations of the embodiment include a task execution configuration.

The plurality of configurations of the embodiment include a runner configuration for monitoring a task database, recovering each task from the task database, providing the recovered task as a task execution configuration, and designating the recovered task to have a pending status .

The task execution configuration of the embodiment executes the task and reports the task execution status to the runner configuration.

The runner configuration of the embodiment reports the status to the task database.

The plurality of configurations of the embodiment include an update configuration for monitoring a task database for a task having a completed status and reporting the status information of the completed task to the platform.

The platform of the embodiment updates a plurality of databases in response to status information.

The metadata of the embodiment is generated by a plurality of agents, wherein the metadata generated by the agent corresponds to the contents accessed by the agent.

The agent of the embodiment generates the metadata by scanning the contents of each file accessed by the agent.

The agent of the embodiment creates metadata by dividing the contents of the file into a plurality of fragments, each fragment comprising a different size configuration of the file.

The various size fragments of the embodiment are between a pre-specified minimum length and a maximum length.

The agent of the embodiment generates metadata by creating a plurality of blobs representing a plurality of fragments, each blob representing a fragment.

The agent of the embodiment generates a plurality of blobs using a data fingerprinting algorithm that executes a hash algorithm over the content structure for each byte of content, the hash algorithm being set to identify a specific pattern of data.

Generating a blob in an embodiment involves generating a description of the blob that contains the value of the hash at the point where the fragment represented by the blob has been separated from the rest of the file.

Generating a blob in an embodiment includes generating an offset value based on a breakpoint of the fragment represented by the blob.

Generating a blob in an embodiment involves generating a hash of the complete content of the blob, wherein the hash of the complete content of the blob is the identifier of the blob.

The generation of a blob in an embodiment includes generating a list of blobs representing the contents of the file.

Generating a blob in an embodiment includes generating a content hash that includes a hash of the list of blobs representing the contents of the file, wherein the content hash is an identifier for the file.

Generating a blob in an embodiment includes generating a name hash containing a hash of the filename corresponding to the file.

Generating a blob in an embodiment includes generating a file hash that includes a hash of a combination of a content hash and a name hash.

The generating of the blob of the embodiment includes generating a path hash that includes a hash of the file name and a file path corresponding to the contents of the file.

Generating a blob in an embodiment includes generating a metadata hash containing a poem by file metadata of the file.

The platform of the embodiment creates a record for the file, and the record includes a blob hash of the file, a content hash, a file hash, a path hash, and a metadata hash.

The plurality of databases of the embodiment includes a library database, which includes records.

Generating a blob in an embodiment includes generating the size of the blob.

The file of the embodiment is described as a list of blobs containing the file.

Each agent in the embodiment stores the blob locally in the client device hosting the agent and sends the previously unreported blob to the central repository of the platform.

The embodiment described herein includes a system including a platform including a processor coupled to a plurality of data. The system includes a grid comprising a plurality of agents coupled to the platform. Each agent of a plurality of agents is an agent of a platform running on the client device. A system is metadata of the contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents. The agent generates the metadata corresponding to the content by hashing a plurality of fragments of the content and provides it to the platform. The platform creates a plurality of tasks including assigning tasks to the plurality of agents, including tasks for controlling at least one of storing, transmitting, and processing content using metadata instead of content. A task is a processing task performed on content accessible by the agent responsible for the task.

Embodiments described herein provide a platform comprising a processor coupled to a q-numbered database, a grid comprising a plurality of agents coupled to the platform, an agent of a platform running on each agent or client device of the plurality of agents, , A metadata-agent of the contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents generates and provides to the platform metadata corresponding to the content by hashing a plurality of fragments of the content, Instead, it uses metadata to create and assign to a plurality of tasks a plurality of tasks including tasks that control at least one of storage, transmission and processing of content, wherein the tasks are stored in content accessible by the agent responsible for the task Is a processing operation performed Including the system.

The embodiments described herein include systems that include a platform that includes a process coupled to a plurality of databases. The system includes a grid comprising a plurality of agents coupled to the platform. Each agent of a plurality of agents is an agent of the platform running on the client device. Each agent in each client device provides the platform with metadata of the contents of the memory accessible by the client device. The platform uses metadata to determine the location of the content, to create a target representing the task to maintain the state of the content, to create a plurality of tasks corresponding to the target, and to access the content corresponding to the task To each task. A task is a processing task indicated by a platform to be executed by an agent, with contents accessible by the agent. Metadata provided by a plurality of agents includes information of a plurality of tasks performed by a plurality of agents.

The embodiment described herein is based on a platform comprising a process connected to a plurality of databases and each agent of a grid-plurality of agents comprising a plurality of agents connected to the platform is an agent of the platform running on the client device, Each agent of the client device provides metadata of the contents of the memory accessible by the client device to the platform and the platform uses the metadata to determine the location of the content, Assigns each task to an agent that accesses the content corresponding to the task, and wherein the task is configured to cause the agent to access content that is accessible by the agent, Processing tasks, It includes a system that includes - provided by the metadata includes information of a plurality of tasks to be performed by a plurality of agents.

The embodiment described herein includes a system including a platform including a processor coupled to a plurality of databases. The system includes a grid comprising a plurality of agents coupled to the platform. Each agent of a plurality of agents is an agent of the platform running on the client device. The system includes metadata of the contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents. Each agent generates metadata corresponding to the contents accessed by the agent and provides it to the platform. Each agent generates metadata by hashing a plurality of fragments of content to generate a plurality of blobs representing a plurality of fragments. The platform uses metadata instead of content to create multiple tasks and assign them to multiple agents. A task is a processing task performed on content accessible by the agent responsible for the task. A plurality of tasks includes tasks that perform at least one of monitoring, storing, transmitting, and processing content.

The implementation described herein includes a platform including a processor coupled to a plurality of databases and a grid comprising a plurality of agents coupled to the platform, wherein each agent of the plurality of agents is an agent of a platform running on the client device, Wherein the metadata includes metadata of the contents of a memory accessible by a plurality of client devices corresponding to the agent, each agent generating and providing metadata to the platform corresponding to the content accessed by the agent, Generating a plurality of blobs representing a plurality of fragments by hashing the fragments and generating a plurality of blobs representing the plurality of fragments, wherein the platform generates a plurality of tasks and assigns them to a plurality of agents by using metadata instead of contents, Accessed by the agent responsible for the task Includes a system including a-and a processing operation performed in the information as possible, a plurality of tasks including the tasks of monitoring, storing, at least one of transmit and process the information.

The embodiments described herein include coupling a platform comprising a processor to a plurality of databases. The method includes forming a grid by connecting a plurality of agents to a platform. Each agent of a plurality of agents is an agent of the platform running on the client device. The method includes creating metadata in each agent and providing metadata to the platform instead of content. The metadata correspond to contents of a memory accessible by a plurality of client apparatuses corresponding to a plurality of agents. The method includes determining the location of the content with metadata. The method includes generating a goal with metadata representing a task for maintaining a state of content. The method includes generating a plurality of tasks corresponding to a target with metadata. The method includes assigning each task to an agent accessing content corresponding to the task. Each task is a processing task that is instructed by the platform and performed by the agent on content accessible by the agent.

The embodiment described herein includes connecting a platform including a processor to a plurality of databases, forming a grid by connecting a plurality of agents to a platform, each agent of a plurality of agents executing on a client device - generating metadata in each agent and providing metadata to the platform in place of contents, the metadata corresponding to contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents; - determining a location of the content with metadata, creating a target having meta data representing a task for maintaining the state of the content, generating a plurality of tasks corresponding to the target with metadata, And an agent accessing the content corresponding to the task Assigning a disk-includes a method including the - each task to an accessible information by the agent, is indicated by the platform, the processing operation being performed by the agents.

The method includes a platform operating as a master controller for a plurality of agents, wherein the plurality of agents interact with the platform as controlled by the plurality of tasks.

The method includes each agent of a plurality of agents functioning independently of the platform and other agents of the plurality of agents.

The method includes, instead of receiving content, a platform for receiving metadata of content, wherein a plurality of client devices hosting a plurality of agents comprises a distributed storage device containing content.

The method includes using a metadata in a plurality of databases to maintain a master index of the contents of a plurality of agents.

The metadata of the embodiment includes data on the location of the contents.

The metadata of the embodiment includes data on the status of the contents.

The metadata of the embodiment includes data for the entities of a plurality of agents.

The metadata of the embodiment includes data about contents that each agent accesses.

The metadata of the embodiment includes information of a plurality of tasks performed by a plurality of agents.

The tasks of an embodiment involve tracking the location of content across a grid.

The tasks of the embodiment involve managing storage of content across a grid.

The tasks of the embodiment involve managing the movement of content across the grid.

The tasks of an embodiment involve managing the processing of content across a grid.

Each task in the embodiment includes a condition of completion for the task.

The method includes a plurality of agents collectively monitoring content as directed by the platform.

The method includes a plurality of agents collectively storing content, as indicated by the platform.

The method includes a plurality of agents collectively transmitting content as indicated by the platform.

The method includes a plurality of agents collectively performing processing operations on content, as indicated by the platform.

The method includes each agent of each client device indexing the contents of memory accessible by the client device.

The plurality of databases of the embodiment includes an agent available to the platform and an agent database containing information of each agent.

Each agent in an embodiment includes at least one library, wherein the library represents an accessing device wherein the agent includes at least one of a read access and a write access.

The plurality of databases of the embodiment includes a library database including a list of libraries corresponding to a plurality of agents, wherein each library of the grid is separately displayed in the library database.

The method includes each agent accessing each library corresponding to an agent.

The plurality of databases of the embodiment includes a target database containing a list of targets, each target of the list of targets being created by a platform and corresponding to at least one library, the target performing a task on a corresponding library content .

The method includes generating a list of targets to include a collection of libraries on which tasks are performed.

Each target in the embodiment corresponds to at least one library and is used by the agent to execute at least one task against the contents of the corresponding library.

The method includes a platform for reading a plurality of libraries of a plurality of agents using a target.

The method includes a platform for identifying at least one of an inconsistency and a difference in content accessible by a plurality of agents using a target.

The method includes a platform for creating at least one task for eliminating at least one of the discrepancies and differences identified in the content using the target.

The plurality of databases of the embodiment includes a task database.

The method includes a platform for creating a task database corresponding to each agent, and the task database includes a task to be performed by a corresponding agent.

The task database of the embodiment includes a description of each task to be performed by the corresponding agent and information necessary for the agent to perform the task.

The plurality of databases of the embodiment includes a capability database that includes information of capabilities of a plurality of agents.

The plurality of databases of the embodiment includes a synchronization database that includes and maintains a record of a plurality of agents.

The synchronization database of the embodiment includes a record of the file status of the contents of a plurality of agents.

The synchronization database of the embodiment includes an entry for each file, the entry including a content hash corresponding to the file, the content hash containing a hash of the list of blobs representing the contents of the file, The blob contains a hash of the fragment of the file in the content, and the fragment is the configuration of the file.

The synchronization database of the embodiment includes an entry for each agent, the entry includes a content hash corresponding to the file of the agent, the content hash includes a hash of the list of blobs representing the contents of the file, Each blob of the file contains a hash of the fragment of the file in the content, and the fragment is the configuration of the file.

The method includes using a plurality of agents to control the transmission of content among the client devices.

The method includes using a plurality of agents to control synchronization of content among client devices, wherein the synchronization of content includes synchronizing the content in response to a change in content.

The transmission of content includes block-level, non-sequential transmission of content.

The transfer of the contents includes transferring the contents of the first block from the second client device to the first client device and transferring the contents of the second block from the third client device to the first client device.

The plurality of tasks include scan tasks.

The scan task of the embodiment includes an agent that regressively monitors the library corresponding to the agent and reports the change in the library to the platform.

Reporting includes locating the library's file containing the changes in the local database of the client device hosting the agent and providing metadata of the local database to the platform.

The plurality of tasks include an indicating task.

The described task includes an agent that copies at least one blob of a file from a first location to a second location, wherein each of the first location and the second location corresponds to a client device associated with the grid.

The at least one blob of the embodiment includes a hash of the fragment of the file in the content, wherein the fragment is a configuration of the file.

The described tasks of the embodiment include the conditions of completion.

The conditions for completion of the embodiment include at least one of receiving the blob corresponding to the written task and identifying the blob to be duplicated during the writing task corresponding to the correct file.

The plurality of tasks of the embodiment includes an upload task that includes copying a file of content from an agent-accessible device to a remote storage device.

The method includes an agent reporting to the platform the addition of a file to content accessible by the agent, wherein the platform, in response to the report, assigns the task to the agent to upload the file.

The method, in response to the agent determining that a file is present on the remote storage device, uploads the file to the remote storage device if it is determined that the file does not exist.

The upload task of the embodiment includes an agent that copies at least one blob of the file from the agent accessible device to the remote storage device.

The at least one blob of the embodiment includes a hash of the fragment of the file, wherein the fragment is a configuration of the file.

The plurality of tasks of the embodiment include delete tasks.

A task including a plurality of states including at least one of standby, pending, and completion of an embodiment, wherein the platform tracks the state of each task of the plurality of tasks.

The method includes, in the client device, each agent that locally maintains tasks assigned to the agent.

The method includes an agent that periodically polls the platform to identify assigned tasks.

The agent of the embodiment is required to complete the task and includes a layer for locating task information located at the remote device.

The layer of embodiments includes an agent that retrieves a local database of client devices hosting the agent.

The layer of the embodiment includes an agent that communicates with at least one peer agent of the plurality of agents to find task information.

The agent of the embodiment includes the entity of the peer agent that owns the task information.

The layer of embodiments includes an agent for recovering task information from a remote storage device.

The method includes receiving an entity of the peer agent from the platform in an ordered list and retrieving task information according to the ordered list.

Each agent in the embodiment includes a plurality of configurations that are executed in parallel.

The plurality of configurations of the embodiment includes a provider configuration that restores the specified task for the agent from the platform and stores the restored task in the task database to the client device hosting the agent.

The plurality of configurations of the embodiment include a task execution configuration.

The plurality of configurations of the embodiment includes a runner configuration for monitoring the task database, restoring each task from the task database, providing the restored task as a task execution configuration, and designating the restored task as having a pending status.

The method includes a task execution good that executes a task and reports the status of the task execution to the runner configuration.

The method includes a runner configuration reporting the status to the task database.

The plurality of configurations of the embodiment includes an update configuration for monitoring the task database to see whether the task has completed status, and reporting the status information of the completed task to the platform.

The method includes a platform for updating a plurality of databases in response to status information.

The method includes a plurality of agents that generate metadata, and the metadata generated by the agent corresponds to the content accessed by the agent.

The method includes an agent that generates metadata by the scanning content of each file accessed by the agent.

The method includes an agent that generates metadata by dividing the contents of the file into a plurality of fragments, each fragment comprising a different size configuration of the file.

Fragments of various sizes of the embodiment are between the pre-specified minimum and maximum lengths.

The method includes an agent that generates metadata by generating a plurality of blobs representing a plurality of fragments, each blob representing a fragment.

The method includes an agent for generating a plurality of blobs using a blob hash, wherein for each byte in the content, the blob hash executes a hash algorithm over the composition of the content, Lt; / RTI >

Generating the blob of an embodiment includes generating a description of the blob that contains the value of the hash at the point at which the fragment represented by the blob has been separated from the rest of the file.

Generating a blob in an embodiment includes generating an offset value based on a breakpoint of the fragment represented by the blob.

Generating a blob in an embodiment includes generating a hash of the complete content of the blob, and the hash of the complete content of the blob is an identifier for the blob.

Generating a blob in an embodiment includes generating a list of blobs that represent the contents of the file.

Generating a blob in an embodiment includes generating a content hash containing a hash of the list of blobs representing the contents of the file, wherein the content hash is an identifier for the file.

Generating a blob in an embodiment includes generating a name hash containing a hash of the filename corresponding to the file.

Generating a blob in an embodiment includes generating a file hash that includes a hash of a combination of a content hash and a name hash.

Generating a blob in an embodiment includes generating a path hash that includes a hash of the file name and a file path corresponding to the contents of the file.

Generating a blob in an embodiment includes generating a metadata hash that includes a hash of the file metadata of the file.

The method includes a platform for generating a record for a file, the record including a blob hash of the file, a content hash, a file hash, a path hash, and a metadata hash.

The plurality of databases of the embodiment includes a library database, wherein the library database includes records.

Generating a blob in an embodiment includes generating the size of the blob.

The file of the embodiment is described as a list of blobs containing the file.

The method includes each agent storing a blob locally at the client device hosting the agent and transmitting the previously unreported blob to the central repository of the platform.

The platform includes a policy database and a rules engine.

The method includes analyzing each file of content.

The method includes describing each file of content as at least one of business content and personal content.

The method includes determining the level of confidentiality of each file of content for business content.

The method includes scanning and extracting key terms from each file of content.

The present invention involves comparing key terms across an enterprise and generating a list of enterprise-specific key terms.

Determining the level of confidentiality includes identifying a particular key term among the key terms.

Generating the metadata includes generating metadata for inclusion of the confidential level of the corresponding content.

The method includes controlling access to each file of content based on the level of confidentiality.

Controlling access involves controlling the viewing of each file of content.

Controlling access involves controlling the downloading of each file of content.

Controlling access includes controlling access to each file of content.

Controlling access involves controlling the copying of each file of content.

Controlling access involves controlling the distribution of each file of content.

The method includes describing each file of content based on inferences made from the content.

The method includes describing each file of content based on the grammar of the content.

The method includes identifying a business content of a content over a location and at least one of a plurality of agents, wherein identifying the business content uses at least one of a document name, a document size, proximity, a key word comparison, .

The method includes controlling collaboration in a plurality of devices accessing a file of content.

The method includes controlling the editing of content in a plurality of devices that simultaneously edit a file of content.

The method includes tracking activity associated with the file of content.

The method includes tracking a modification history of a file of content.

The method includes managing mobile devices, including accessing and monitoring content via a mobile device.

Mobile device management involves tracking the location of the mobile device.

Mobile device management includes controlling access to content based on location.

Mobile device management involves including mobile autonomous tracking data.

The method includes connecting the console to a platform, the console including automated activity monitoring, auditing and reporting related to the content.

The method involves controlling through console activity related to the content.

This method involves controlling the position through the console

Controlling activity controls controlling the viewing of each file of content, controlling downloading of each file of content, controlling access to each file of content, and copying each file of content , And controlling distribution of each file of content.

The embodiments described herein include coupling a platform comprising a processor to a plurality of databases. The method includes forming a grid comprising a plurality of agents coupled to the platform. Each agent is an agent of the platform running on the client device. The method includes generating, at each agent, metadata by hashing a plurality of fragments of content accessible by the agent. The metadata may be stored in a memory accessible by a plurality of client devices corresponding to the plurality of agents It corresponds to contents. The present invention includes providing metadata to the platform instead of content. The present invention includes generating a plurality of tasks, the tasks including at least one of storing, transmitting and processing content, as metadata. A task is a processing task that is performed on content accessible by the agent responsible for the task. The present invention includes assigning a plurality of tasks to a plurality of agents.

The embodiment described herein includes connecting a platform comprising a processor to a plurality of databases and forming a grid comprising a plurality of agents coupled to the platform, each agent being an agent of a platform running on the client device - generating, at each agent, metadata by hashing a plurality of fragments of content accessible by the agent, wherein the metadata corresponds to a content of memory accessible by a plurality of client devices corresponding to the plurality of agents - providing metadata to the platform instead of content and creating a plurality of tasks including tasks that control at least one of storing, transmitting, and processing content with metadata, Performed on content accessible by an agent that And a step of assigning, and a plurality of tasks and a plurality of agent-Rosedale washing operation being.

The embodiments described herein include coupling a platform comprising a processor to a plurality of databases. The method includes forming a grid comprising a plurality of agents coupled to the platform. Each agent is an agent of the platform running on the client device. The method includes providing, by each agent of each client device, metadata of the contents of memory accessible by the client device to the platform. The method includes determining the location of the content with metadata. The method includes creating a target that represents a task for maintaining the state of the content with metadata. The method includes generating a plurality of tasks corresponding to a target with metadata. The method includes assigning each task to an agent accessing content corresponding to the task. A task is a processing task that is instructed by the platform for content accessible by an agent and performed by an agent. The metadata provided by a plurality of agents includes information of a plurality of tasks performed by a plurality of agents.

The embodiment described herein includes connecting a platform comprising a processor to a plurality of databases and forming a grid comprising a plurality of agents coupled to the platform, each agent being an agent of a platform running on the client device - providing, by each agent of each client device, metadata of the contents of a memory accessible by the client device to the platform; determining the location of the content by the metadata; Creating a plurality of tasks corresponding to a target with metadata; and assigning each task to an agent accessing content corresponding to the task, the task comprising the steps of: , By the platform for content accessible by the agent And wherein the metadata provided by the plurality of agents includes information of a plurality of tasks performed by the plurality of agents.

The embodiments described herein include establishing a connection between a platform comprising a processor and a plurality of databases. The method includes forming a grid by connecting a plurality of agents to a platform. Each agent of a plurality of agents is an agent of the platform running on the client device. The method includes generating metadata in each agent indicating the contents of a memory accessible by a plurality of client devices corresponding to the plurality of agents. The generating includes hashing a plurality of fragments of the content to generate a plurality of blobs representing the plurality of fragments. The method includes providing metadata to the platform instead of content. The method includes generating a plurality of tasks with metadata. A task is a processing task performed on content accessible by the agent responsible for the task. The plurality of tasks include at least one task of monitoring, storing, transmitting, and processing the contents. And assigning the plurality of tasks to the plurality of agents.

Comprising: establishing a connection between a platform comprising a processor and a plurality of databases; forming a grid by connecting a plurality of agents to a platform, wherein each agent of the plurality of agents is an agent of a platform running on the client device; And metadata in each agent indicating the contents of a memory accessible by a plurality of client devices corresponding to the plurality of agents, wherein the generating comprises hashing a plurality of fragments of the content to represent a plurality of fragments The method comprising the steps of: providing metadata to the platform instead of contents; and creating a plurality of tasks with metadata, wherein the task includes content that is accessible by the agent responsible for the task And a plurality of tasks are processing tasks Wherein the at least one task comprises at least one task of monitoring, storing, transmitting, and processing a task, and assigning the plurality of tasks to the plurality of agents.

As described above, a computer network suitable for use with the embodiments described herein may be a local area network (LAN), a wide area network (WAN), the Internet, or the World Wide Web, the public Internet, , Public network, mobile network, cellular network, value added network (VAD), and the like. The computing device connected to or coupled to the network may be a personal computer, a workstation server, a minicomputer, a mainframe computer, a laptop computer, a mobile computer, a palm top computer, a portable computer, a mobile phone, a TV set- May be any microprocessor control device that allows access to the network, including terminal devices such as a combination. A computer network may include one or more LANs, WANs, the Internet, and a computer. The computer can be used as a server, a client, or a combination thereof.

The configurations described above may be a single system, multiple systems, and / or a configuration of a geographically separated system. The configurations described above may also be sub-configurations or subsystems of a single system, multiple systems, and / or geographically separated systems. The configurations described above may be connected to one or more configurations (not shown) of a host system or a system coupled to the host system.

The configurations described herein include or execute in conjunction with a processing system. The processing system may include a processor-based device or a collection of components of a computing device or a processing system or device that operate together, as is known to those skilled in the art. For example, the processing system may include one or more of a portable computer, a portable communication device operating in a communication network, and / or a network server. The portable computer may be any of a number of or a combination selected from a personal computer, a personal digital assistant, a portable computing device, and a portable communication device, but is not limited thereto. The processing system may include a configuration within a large computer system.

The processing system of one embodiment includes at least one processor and at least one memory device or system. The processing system also includes or is connected to one or more databases. As used herein, the term "processor" generally refers to a logic processing unit such as one or more central processing units (CPUs), digital signal processors (DSPs), application specific integrated circuits (ASICs)

Where the context of the specification and the claims is not clear, it is to be understood that the terms "comprises", "including", etc. are not intended to be exclusive, and have a generic meaning. That is, " including, but not limited to, " Words using single or plural meanings also include plural or single meanings, respectively. It is also to be understood that the words "in this specification "," in the following ", "above "," below ", and similar terms are used herein to mean the entirety of the specification, When the word "or" is used in connection with two or more items, such a word includes both of the following interpretations of the word. Any item in the list, all items in the list, and any combination of the items in the list. The above description of embodiments and corresponding systems and methods is not to be construed as including both, and is not intended to limit the systems and methods of the present invention to the exact forms described.

Specific embodiments of the systems and methods have been described herein for purposes of explanation and various modifications are possible within the scope of the systems and methods of the present invention as will be appreciated by those skilled in the art. While specific embodiments and examples of system implementation are described for illustrative purposes, various equivalent modifications are possible within the scope of the present systems and methods, as will be appreciated by those skilled in the art. The provided systems and methods may be applied to other systems and methods as well as the systems and methods described above.

The elements and acts of the various embodiments described herein may be combined to provide further embodiments. These and other changes may be made to the system and method in light of the above detailed description.

Claims (125)

Connecting a platform including a processor to a plurality of databases,
Forming a grid by connecting a plurality of agents to a platform, each agent of the plurality of agents being an agent of a platform running on the client device;
Generating metadata in each agent and providing metadata to the platform instead of contents, the metadata corresponding to contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents,
Determining a location of the content with metadata,
Creating a target having metadata indicating an operation for maintaining a state of content;
Generating a plurality of tasks corresponding to targets with metadata; and
Assigning each task to an agent accessing content corresponding to the task, wherein each task is a content task accessible by the agent, the task being instructed by the platform and performed by the agent. 2. The method of claim 1, comprising a platform operating as a master controller for a plurality of agents, wherein the plurality of agents interact with the platform as controlled by the plurality of tasks. 2. The method of claim 1, wherein each agent of the plurality of agents functions independently of the platform and the other agents of the plurality of agents. The system of claim 1, wherein instead of receiving content, a plurality of client devices hosting a plurality of agents, including a platform for receiving metadata of content, comprises a distributed storage device containing content How to. 2. The method of claim 1, comprising using a metadata in a plurality of databases to maintain a master index of the content of a plurality of agents. 2. The method of claim 1, wherein the metadata includes data on the location of the content. 2. The method of claim 1, wherein the metadata includes data on the status of the content. The method of claim 1, wherein the metadata includes data for an entity of a plurality of agents. 2. The method of claim 1, wherein the metadata includes data about content that each agent accesses. The method of claim 1, wherein the metadata includes information of a plurality of tasks performed by a plurality of agents. 2. The method of claim 1, wherein the task is associated with tracking the location of the content across the grid. 6. The method of claim 1, wherein the task is associated with managing storage of content across a grid. The method of claim 1, wherein the task is associated with managing movement of content across the grid. 2. The method of claim 1, wherein the task is associated with managing the processing of the content across the grid. The method of claim 1, wherein each task includes a condition of completion for the task. 2. The method of claim 1, wherein the plurality of agents collectively monitor the content as directed by the platform. 2. The method of claim 1, wherein the plurality of agents collectively store the content as directed by the platform. 2. The method of claim 1, wherein the plurality of agents collectively transmit the content as directed by the platform. 2. The method of claim 1, wherein the plurality of agents collectively perform processing operations on the content, as indicated by the platform. 2. The method of claim 1, comprising each agent of each client device indexing the contents of memory accessible by the client device. 2. The method of claim 1, wherein the plurality of databases comprises an agent available to the platform and an agent database containing information of each agent. 2. The method of claim 1, wherein each agent comprises at least one library, wherein the library represents an accessing device wherein the agent includes at least one of a read access and a write access. 23. The method of claim 22, wherein the plurality of databases comprises a library database comprising a list of libraries corresponding to a plurality of agents, wherein each library of grids appears separately in a library database. 24. The method of claim 23, comprising each agent accessing each library corresponding to an agent. 23. The system of claim 22, wherein the plurality of databases comprises a target database comprising a list of targets, each target of the list of targets being generated by a platform, corresponding to at least one library, ≪ / RTI > is used to perform an operation on a server. 26. The method of claim 25, comprising generating a list of targets to include a collection of libraries on which tasks are performed. 26. The method of claim 25, wherein each goal corresponds to at least one library and is used by an agent to execute at least one task for the contents of the corresponding library. 26. The method of claim 25, wherein the platform uses a target to read a plurality of libraries of a plurality of agents. 26. The method of claim 25, wherein the platform identifies at least one of a discrepancy and a difference in content accessible by the plurality of agents using the target. 30. The method of claim 29, wherein the platform uses the target to create at least one task for removing at least one of the discrepancies and differences identified in the content. 2. The method of claim 1, wherein the plurality of databases comprises a task database. 32. The method of claim 31, wherein the platform generates a task database corresponding to each agent, the task database comprising a task to be performed by a corresponding agent. 33. The method of claim 32, wherein the task database includes a description of each task to be performed by the corresponding agent and information that the agent needs to perform the task. 2. The method of claim 1, wherein the plurality of databases comprises a capability database that includes information of capabilities of a plurality of agents. 2. The method of claim 1, wherein the plurality of databases comprises a synchronization database that includes and maintains a record of a plurality of agents. 36. The method of claim 35, wherein the synchronization database comprises a record of the file status of the contents of a plurality of agents. 37. The method of claim 36, wherein the synchronization database includes an entry for each file, the entry comprising a content hash corresponding to the file, the content hash comprising a hash of the list of blobs representing the contents of the file, Each of the blobs in the list comprising a hash of a fragment of a file in the content, the fragment being a configuration of the file. 38. The method of claim 36, wherein the synchronization database includes an entry for each agent, the entry includes a content hash corresponding to the file of the agent, the content hash includes a hash of the list of blobs representing the contents of the file, Wherein each blob in the list of blobs contains a hash of the fragment of the file in the content, and the fragment is a configuration of the file. 2. The method of claim 1, wherein the platform uses a plurality of agents to control the transfer of content to the client device. 40. The method of claim 39, wherein the platform controls synchronization of content among the client devices using a plurality of agents, wherein synchronization of content comprises synchronizing content in response to changes in content. 40. The method of claim 39, wherein the transfer of content comprises a block-level, non-sequential transfer of content. 42. The method of claim 41, wherein the transfer of content comprises transferring the contents of the first block from the second client device to the first client device and transferring the contents of the second block from the third client device to the first client device ≪ / RTI > 2. The method of claim 1, wherein the plurality of tasks comprise scan tasks. 44. The method of claim 43, wherein the scan task comprises an agent that regressively monitors the library corresponding to the agent and reports the change in the library to the platform. 45. The method of claim 44, wherein reporting includes locating the library's file containing the changes in the local database of the client device hosting the agent and providing metadata of the local database to the platform. 2. The method of claim 1, wherein the plurality of tasks comprises an indicating task. 47. The method of claim 46, wherein the writing task comprises an agent that copies at least one blob of the file from a first location to a second location, wherein each of the first and second locations corresponds to a client device associated with the grid Lt; / RTI > 49. The method of claim 47, wherein the at least one blob comprises a hash of a fragment of a file in the content, the fragment being a configuration of the file. 47. The method of claim 46, wherein the written task comprises a condition of completion. 50. The method of claim 49, wherein the condition of completion includes at least one of receiving the blob corresponding to the written task and identifying the blob to be duplicated during the writing task corresponding to the correct file . 2. The method of claim 1, wherein the plurality of tasks comprises an upload task comprising copying a file of content from an agent accessible device to a remote storage device. 52. The method of claim 51, wherein the agent reports to the platform the addition of the file to the content accessible by the agent, and the platform assigns the task to the agent in response to the report to upload the file. 53. The method of claim 52, wherein, in response to the agent determining that the file is present on the remote storage device, if the file is determined to be absent, the file is uploaded to the remote storage device. 52. The method of claim 51, wherein the upload task comprises an agent that copies at least one blob of the file from the agent accessible device to the remote storage device. 55. The method of claim 54, wherein the at least one blob comprises a hash of a fragment of a file, wherein the fragment is a configuration of a file. 2. The method of claim 1, wherein the plurality of tasks comprise delete tasks. 2. The method of claim 1, wherein the task includes a plurality of states including at least one of waiting, pending, and completed, wherein the platform tracks the state of each task of the plurality of tasks. 2. The method of claim 1, wherein each agent locally maintains a task assigned to an agent at a client device. 59. The method of claim 58, wherein the agent periodically polls the platform to identify an assigned task. 2. The method of claim 1, wherein the agent is required to complete the task and comprises a layer for locating task information located at the remote device. 61. The method of claim 60, wherein the layer comprises an agent that retrieves a local database of client devices hosting the agent. 63. The method of claim 61, wherein the layer comprises an agent in communication with at least one peer agent of the plurality of agents to find task information. 63. The method of claim 62, wherein the agent comprises an entity of a peer agent that owns task information. 63. The method of claim 62, wherein the layer comprises an agent for recovering task information from a remote storage device. 65. The method of claim 64, wherein the agent receives the entity of the peer agent in the ordered list from the platform and retrieves the task information according to the ordered list. 2. The method of claim 1, wherein each agent comprises a plurality of configurations that are executed in parallel. 67. The method of claim 66, wherein the plurality of configurations includes a provider configuration for recovering a task designated for the agent from the platform and storing the recovered task in the task database to the client device hosting the agent. 68. The method of claim 67, wherein the plurality of configurations comprises a task execution configuration. 69. The system of claim 68, wherein the plurality of configurations includes a runner configuration for monitoring a task database, recovering each task from a task database, providing the recovered task as a task execution configuration, and designating the recovered task as having a pending status . ≪ / RTI > 70. The method of claim 69, wherein the task execution configuration executes the task and reports the status of the task execution to the runner configuration. 71. The method of claim 70, wherein the runner configuration reports the status to the task database. 72. The method of claim 71, wherein the plurality of configurations includes an update configuration for monitoring a task database to see if the task has a completed status and reporting the status information of the completed task to the platform. 73. The method of claim 72, wherein the platform updates the plurality of databases in response to the status information. The method of claim 1, wherein the plurality of agents generate metadata, wherein the metadata generated by the agent corresponds to the content accessed by the agent. 75. The method of claim 74, wherein the agent generates metadata by the scanning content of each file accessed by the agent. 76. The method of claim 75, wherein the agent generates metadata by dividing the contents of the file into a plurality of fragments, each fragment comprising a different size configuration of the file. 77. The method of claim 76, wherein the fragments of various sizes are between a pre-specified minimum length and a maximum length. 76. The method of claim 76, wherein the agent generates metadata by generating a plurality of blobs representing a plurality of fragments, each blob representing a fragment. 80. The method of claim 76, wherein the agent generates a plurality of blobs using a blob hash, wherein the blob hash performs a hash algorithm over the content's configuration for each byte in the content, And to identify the identified pattern. 80. The method of claim 79, wherein generating the blob produces a description of the blob that includes the value of the hash at the point at which the fragment represented by the blob has been separated from the rest of the file. 79. The method of claim 80, wherein generating the blob generates an offset value based on a breakpoint of the fragment represented by the blob. 83. The method of claim 81, wherein generating the blob includes generating a hash of the complete content of the blob, wherein the hash of the complete content of the blob is an identifier for the blob. 83. The method of claim 82, wherein generating the blob produces a list of blobs representing the contents of the file. 83. The method of claim 83, wherein generating the blob includes generating a content hash that includes a hash of the list of blobs representing the content of the file, wherein the content hash is an identifier for the file. 85. The method of claim 84, wherein generating the blob generates a name hash containing a hash of the file name corresponding to the file. The method of claim 85, wherein generating the blob generates a file hash that includes a hash of the combination of the content hash and the name hash. The method of claim 86, wherein generating the blob generates a path hash that includes a hash of the file name and a file path corresponding to the contents of the file. 90. The method of claim 87, wherein generating the blob generates a metadata hash that includes a hash of the file metadata of the file. 90. The method of claim 88, wherein the platform generates a record for the file, wherein the record includes a blob hash of the file, a content hash, a file hash, a path hash, and a metadata hash. 90. The method of claim 89, wherein the plurality of databases comprises a library database, wherein the library database comprises records. 80. The method of claim 79, wherein generating a blob produces a magnitude of the blob. 80. The method of claim 79, wherein the file is described as a list of blobs containing the file. 80. The method of claim 79, wherein each agent stores the blob locally at the client device hosting the agent and sends the previously unreported blob to the central repository of the platform. 2. The method of claim 1, wherein the platform comprises a policy database and a rules engine. 2. The method of claim 1, wherein each file of content is analyzed. The method of claim 95, wherein each file of content is described as at least one of a business content and a personal content. 96. The method of claim 96, wherein the confidential level of each file of content is determined for business content. The method of claim 96, wherein key terms are scanned and extracted from each file of content. 98. The method of claim 98, wherein key terms are compared across an enterprise and a list of enterprise-specific key terms is generated. 98. The method of claim 98, wherein determining the confidentiality level identifies a particular key term of the key terms. 97. The method of claim 97, wherein generating the metadata generates metadata for including the level of confidentiality of the corresponding content. 97. The method of claim 97, comprising controlling access to each file of content based on the level of confidentiality. 103. The method of claim 102, wherein controlling access controls viewing each file of content. 103. The method of claim 102, wherein controlling access controls downloading of each file of content. 103. The method of claim 102, wherein controlling access controls access to each file of content. 103. The method of claim 102, wherein controlling access controls copying of each file of content. 103. The method of claim 102, wherein controlling access controls distribution of each file of content. The method of claim 95, wherein each file of content is described based on an inference made from the content. The method of claim 95, wherein each file of content is described based on a grammar of the content. 95. The method of claim 95, further comprising identifying business content of the content across at least one of the location and the plurality of agents, wherein identifying the business content includes at least one of: document name, document size, proximity, ≪ / RTI > 2. The method of claim 1, wherein the collaboration is controlled in a plurality of devices accessing a file of content. 111. The method of claim 111, controlling the editing of content in a plurality of devices that simultaneously edit a file of content. 111. The method of claim 111, wherein the activity is tracked in association with a file of content. 111. The method of claim 111, wherein a modification history of a file of content is tracked. The method of claim 1, comprising managing mobile devices, including accessing and monitoring content via a mobile device. 116. The method of claim 115, wherein mobile device management tracks the location of the mobile device. 116. The method of claim 116, wherein mobile device management controls access to content based on location. 116. The method of claim 115, wherein mobile device management comprises mobile autonomic tracking data. The method of claim 1, comprising connecting a console to a platform, the console including automated activity monitoring, auditing and reporting related to the content. 120. The method of claim 119, comprising controlling through console activity associated with the content. 120. The method of claim 119, comprising controlling the position through the console. 120. The method of claim 120, wherein controlling the activity comprises controlling the viewing of each file of content, controlling downloading of each file of content, controlling access to each file of content, Controlling copying, and controlling distribution of each file of content. ≪ Desc / Clms Page number 16 > Connecting a platform including a processor to a plurality of databases,
Forming a grid comprising a plurality of agents coupled to a platform, each agent being an agent of a platform running on a client device;
In each agent, generating metadata by hashing a plurality of fragments of content accessible by the agent, the metadata corresponding to contents of a memory accessible by a plurality of client devices corresponding to a plurality of agents,
Providing metadata to the platform instead of content,
The method comprising: generating a plurality of tasks, the tasks including at least one of storing, transmitting, and processing contents, as metadata, the tasks being processing tasks performed on content accessible by the agent responsible for the task; And
Assigning a plurality of tasks to a plurality of agents. Connecting a platform including a processor to a plurality of databases,
Forming a grid comprising a plurality of agents coupled to a platform, each agent being an agent of a platform running on a client device;
Providing, by each agent of each client device, metadata of the contents of memory accessible by the client device to the platform;
Determining a location of the content with metadata,
Creating a target representing an operation for maintaining the state of the content with metadata,
Generating a plurality of tasks corresponding to targets with metadata; and
Assigning each task to an agent accessing content corresponding to the task, the task being a processing task instructed by the platform and performed by the agent for content accessible by the agent, Wherein the information includes information of a plurality of tasks performed by a plurality of agents. Establishing a connection between a platform comprising a processor and a plurality of databases,
Forming a grid by connecting a plurality of agents to a platform, each agent of the plurality of agents being an agent of a platform running on the client device;
The method comprising: generating metadata in each agent representing content of a memory accessible by a plurality of client devices corresponding to a plurality of agents, the generating comprising hashing a plurality of fragments of content to generate a plurality of fragments representing a plurality of fragments Generating a blob,
Providing metadata to the platform instead of content,
Generating a plurality of tasks with metadata, the task being a processing task performed on contents accessible by the agent responsible for the task, and the plurality of tasks including at least one task of monitoring, storing, transmitting, and processing the contents - and, and
Assigning a plurality of tasks to a plurality of agents.

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