Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
  • H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
  • G06F21/60—Protecting data
  • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L67/00—Network arrangements or protocols for supporting network services or applications
  • H04L67/01—Protocols
  • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
  • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
  • H04L9/0891—Revocation or update of secret information, e.g. encryption key update or rekeying
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
  • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
  • H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
  • H04L9/3239—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions involving non-keyed hash functions, e.g. modification detection codes [MDCs], MD5, SHA or RIPEMD
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/02—Services making use of location information
  • H04W4/029—Location-based management or tracking services
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
  • H04W4/30—Services specially adapted for particular environments, situations or purposes
  • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information

Definitions

• the disclosure relates to the field of asset tracking and management, more specifically to the field of crypto-ledger or block chain technology and its uses for managing inventory assets.
• a system and method for dynamic geospatially- referenced cyber-physical infrastructure inventory and asset management, including a business operating system, parameter evaluation engine, at least one cyber-physical asset, at least one crypt-ledger, a network, and the ability to represent data in Markov State Models and finite state machines. It is also possible for the system and methods provided herein to be applied to use case of a mobile or stationary processing facility, which may process objects and send status updates on what objects it is processing to an operating system either remotely or locally hosted, for continuous monitoring.
• Fig. 1 is a diagram of an exemplary architecture of a system for the capture and storage of time series data from sensors with heterogeneous reporting profiles according to a preferred aspect of the invention.
• Rg. 2 is a diagram of an exemplary architecture of a business operating system according to a preferred aspect of the invention.
• FIG. 3 is a diagram of an exemplary architecture of an automated planning service cluster and related modules according to a preferred aspect.
• FIG. 4 is a system diagram illustrating connections between core components of the invention for geo-locaung and tracking the status of cyber-physical assets, according to a preferred aspect.
• Rg. 5 is a method diagram illustrating key steps in the communication between cyber- physical assets and remote servers, according to a preferred aspect
• Rg. 6 is a method diagram illustrating key steps in a business operating system interacting with data received from cyber physical assets in databases to verify updates in a cryptographic ledger, according to a preferred aspect
• Fig. 7 is a method diagram illustrating several steps in the use of smart contracts combined with cyber-physical assets, according to a preferred aspect
• Rg. 8 is a method diagram illustrating key steps in the function of a parametric evaluation engine, according to a preferred aspect
• Rg. 9 is a block diagram illustrating an exemplary hardware architecture of a computing device.
• Rg. 10 is a block diagram illustrating an exemplary logical architecture for a client device.
• Rg. 11 is a block diagram showing an exemplary architectural arrangement of clients, servers, and external services.
• Rg. 12 is another block diagram illustrating an exemplary hardware architecture of a computing device. DETAILED DESCRIPTION
• Devices that are in communication with each other need not be in continuous communication with each other, unless expressly specified otherwise.
• devices that are in communication with each other may communicate directly or indirectly through one or more communication means or intermediaries, logical or physical.
• steps may be performed simultaneously despite being described or implied as occurring non simultaneously (e.g., because one step is described after the other step).
• the illustration of a process by its depiction in a drawing does not imply that the illustrated process is exclusive of other variations and modifications thereto, does not imply that the illustrated process or any of its steps are necessary to one or more of the aspects, and does not imply that the illustrated process is preferred.
• steps are generally described once per aspect, but this does not mean they must occur once, or that they may only occur once each time a process, method, or algorithm is carried out or executed. Some steps may be omitted in some aspects or some occurrences, or some steps may be executed more than once in a given aspect or occurrence.
• a "swimlane* is a communication channel between a time series sensor data reception and apportioning device and a data store meant to hold the apportioned data time series sensor data.
• a swimlane is able to move a specific, finite amount of data between the two devices. For example a single swimlane might reliably carry and have incorporated into the data store, the data equivalent of 5 seconds worth of data from 10 sensors in 5 seconds, this being its capacity. Attempts to place 5 seconds worth of data received from 6 sensors using one swimlane would result in data loss.
• a "metaswimlane'' is an as-needed logical combination of transfer capacity of two or more real swimlanes that is transparent to the requesting process. Sensor studies where the amount of data received per unit time is expected to be highly
• Fig. 1 is a diagram of an exemplary architecture of a system for the capture and storage of time series data from sensors with heterogeneous reporting profiles according to a preferred aspect of the invention.
• a plurality of sensor devices 1 lOa-n stream data to a collection device, in this case a web server acting as a network gateway 115.
• sensors 1 lOa-n can be of several forms, some non-exhaustive examples being: physical sensors measuring humidity, pressure, temperature, orientation, and presence of a gas; or virtual such as programming measuring a level of network traffic, memory usage in a controller, and number of times the word "refill" is used in a stream of email messages on a particular network segment, to name a small few of the many diverse forms known to the art.
• the sensor data is passed without transformation to the data management engine 120, where it is aggregated and organized for storage in a specific type of data store 125 designed to handle the multidimensional time series data resultant from sensor data.
• Raw sensor data can exhibit highly different delivery characteristics. Some sensor sets may deliver low to moderate volumes of data continuously.
• the data stream management engine 120 would hold incoming data in memory, keeping only the parameters, or "dimensions'' from within the larger sensor stream that are pre decided by the administrator of the study as important and instructions to store them transmitted from the administration device 112. The data stream management engine 120 would then aggregate the data from multiple individual sensors and apportion that data at a predetermined interval, for example, every 10 seconds, using the timestamp as the key when storing the data to a multidimensional time series data store over a single swimlane of sufficient size.
• the invention also can make use of event based storage triggers where a predetermined number of data receipt events, as set at the administration device 112, triggers transfer of a data block consisting of the apportioned number of events as one dimension and a number of sensor ids as the other.
• the system time at conunitment or a time stamp that is part of the sensor data received is used as the key for the data block value of the value-key pair.
• the invention can also accept a raw data stream with commitment occurring when the accumulated stream data reaches a predesigned size set at the adniinistration device 112.
• the embodiment of the invention can, if capture parameters pre-set at the administration device 112, combine the data movement capacity of two or more swimlanes, the combined bandwidth dubbed a metaswimlane, transparently to die committing process, to accommodate the influx of data in need of commitment All sensor data, regardless of deliver ) ' circumstances are stored in a multidimensional time series data store 125 which is designed for very low overhead and rapid data storage and minimal maintenance needs to sap resources.
• the embodiment uses a key-value pair data store examples of which are Riak, Redis and Berkeley DB for their low overhead and speed, although the invention is not specifically tied to a single data store type to the exclusion of others known in the art should another data store with better response and feature characteristics emerge. Due to factors easily surmised by those knowledgeable in the art, data store commitment reliability is dependent on data store data size under the conditions intrinsic to time series sensor data analysis. The number of data records must be kept relatively low for the herein disclosed purpose. As an example one group of developers restrict the size of their multidimensional time series key-value pair data store to
• the archival storage is included 130.
• This archival storage might be locally provided by the user, might be cloud based such as that offered by Amazon Web Services or Google or could be any other available very large capacity storage method known to those skilled in the art
• data_spec* might be replaced by a list of individual sensors from a larger array of sensors and each sensor in die list might be given a human readable identifier in the format "sensor AS identifier", "unit” allows the researcher to assign a periodicity for the sensor data such as second (s), minute (m), hour (h).
• transformational filters which include but a not limited to: mean, median, variance, standard deviation, standard linear interpolation, or Kalman filtering and smoothing, may be applied and then data formatted in one or more formats examples of with are text, JSON, KML, GEOJSON and TOPOJSON among others known to the art, depending on the intended use of the data.
• FIG. 2 is a diagram of an exemplary architecture of a business operating system 200 according to a preferred aspect.
• ELASTIC BEANSTALKTM both used for standards compliance and ease of development
• the directed computational graph retrieves one or more streams of data from a plurality of sources, which includes, but is in no way not limited to, a number of physical sensors, web-based questionnaires and surveys, monitoring of electronic infrastructure, crowd sourcing campaigns, and human input device information.
• data may be split into two identical streams, wherein one sub-stream may be sent for batch processing and storage while the other sub- stream may be reformatted for transformation pipeline analysis.
• the data is then transferred to general transformer service 260 for linear data transformation as part of analysis or decomposable transformer service 250 for branching or iterative transformations that are part of analysis.
• the directed computational graph 255 represents all data as directed graphs where the transformations are nodes and the result messages between transformations edges of the graph. These graphs which contain considerable intermediate transformation data are stored and further analyzed within graph stack module 245.
• High volume web crawling module 215 uses multiple server hosted preprogrammed web spiders to find and retrieve data of interest from web-based sources that are not well lagged by conventional web crawling technology.
• Multiple dimension time series database module 220 receives data from a large plurality of sensors that may be of several different types.
• the module is designed to accommodate irregular and high volume surges by dynamically allotting network bandwidth and server processing channels to process the incoming data.
• Data retrieved by the multidimensional time series database 220 and the high volume web crawling module 215 may be further analyzed and transformed into task optimized results by the directed computational graph 255 and associated general transformer service 250 and decomposable transformer service 260 modules.
• Results of the transformative analysis process may then be combined with further client directives, additional business rules and practices relevant to the analysis and situational information external to the already available data in the automated planning service module 290 which also runs powerful predictive statistics functions and machine learning algorithms to allow future trends and outcomes to be rapidly forecast based upon the cun ent system derived results and choosing each a plurality of possible business decisions.
• the automated planning service module 230 may propose business decisions most likely to result is the most favorable business outcome with a usably high level of certainty.
• the business outcome simulation module 225 coupled with the end user facing observation and state estimation service 240 allows business decision makers to investigate the probable outcomes of choosing one pending course of addon over another based upon analysis of the current available data.
• the pipelines operations department has reported a very small reduction in crude oil pressure in a section of pipeline in a highly remote section of territory. Many believe the issue is entirely due to a fouled, possibly failing flow sensor, others believe that it is a proximal upstream pump that may have foreign material stuck in it. Correction of both of these possibilities is to increase the output of the effected pump to hopefully clean out it or the fouled sensor.
• Fig. 3 is a diagram of an exemplary architecture of an automated planning service module and related modules 300 according to an embodiment of the invention. Seen here is a more detailed view of the automated planning service module 230 as depicted in Fig. 2.
• the module functions by receiving business decision or business venture candidates as well as relevant currently available related data and any campaign analysis modification commands through a client interface 305.
• the module may also be used provide transformed data or run parameters to the action outcome simulation module 225 to seed a simulation prior to run or to transform intermediate result data isolated from one or more actors operating in the action outcome simulation module 225, during a simulation run.
• Contemplated actions may be broken up into a plurality of constituent events that either act towards the fulfillment of the venture under analysis or represent the absence of each event by the discrete event simulation module 311 which then makes each of those events available for information theory based statistical analysis 312, which allows the current decision events to be analyzed in light of similar events under conditions of varying dissimilarity using machine learned criteria obtained from that previous data; results of tins analysis in addition to other factors may be analyzed by an uncertainty estimation module 313 to further nine the level of confidence to be included with the finished analysis.
• Confidence level would be a weighted calculation of the random variable distribution given to each event analyzed. Prediction of the effects of at least a portion of the events involved with a business venture under analysis within a system as complex as anything from the microenvironment in which the client business operates to more expansive arenas as the regional economy or further, from the perspective of success of the client business is calculated in dynamic systems extraction and inference module 314, which use, among other tools algorithms based upon Shannon entropy, Hartley entropy and mutual information dependence theory.
• the invention is therefore designed to run on expandable dusters 315, in a distributed, modular, and extensible approach, such as, but not exclusively, offerings of Amazon's AWS.
• these analysis jobs may run for many hours to completion and many clients may be anticipating long waits for simple "what if" options which will not affect their business operations in the near term while other clients may have come upon a pressing decision situation where they need alternatives as soon as possible.
• This is accommodated by the presence of a job queue that allows analysis jobs to be implemented at one of multiple priority levels from low to urgent.
• job priorities can also be changed during run without loss of progress using the priority based job queue 318.
• Structured plan analysis result data may be stored in either a general purpose automated planning engine executing Action Notation Modeling Language (ANML) scripts for modeling which can be used to prioritize both human and machine-oriented tasks to maximize reward functions over finite time horizons 317 or through the graph-based data store 245, depending on the specifics of the analysis in complexity and time run.
• ANML Action Notation Modeling Language
• results of analyses may be sent to one of two client facing presentation modules, the action outcome simulation module 225 or the more visual simulation capable observation and state estimation module 240 depending on the needs and intended usage of the data by the client
• Fig. 4 is a system diagram illustrating connections between core components of the invention for geo-locating and tracking the status of cyber-physical assets, according to a preferred aspect.
• a business operating system 410 operates an optimization engine 411, parametric evaluation engine 412, and uses abstract data representations 413 including Markov State Models (MSM) 414 and abstract representations of finite state machines 415 to read, modify, and generally- operate on data.
• MSM Markov State Models
• a business operating system 410 such as this is connected to a network 450, which may be an intranet, the internet, a local area connection, or any one of many other configurations of networks.
• At least one database 420 which holds information including a crypto-ledger 421, an implementation of a blockchain data construct, which will be expounded upon in later figures.
• a cyber physical asset 430, 440 which may hold any number of sensors or data according to a specific implementation, and have geqJSON 431, 441 data with which to record their geo-physical location.
• a cyber-physical asset 430, 440 may be a delivery crate with a possible plurality of sensors and computers embedded or attached to the crate in some way, or may be an object inside a mundane crate such as a piece of research equipment which may communicate with a business operating system 410 during transit, or may be a stationary object such as research equipment, computer systems, and more, which are capable of sending status updates at least consisting of geqJSON 431, 441 information regarding their geophysical location over a network 450.
• a business operating system may use a Markov State Model (MSM) 414 as a tool for data representation of the states of cyber-physical assets which send status updates in this way, and may or may not reduce a MSM to a finite state machine representation 415 with or without stochastic elements, according to a prefei-red aspect.
• MSM Markov State Model
• These data representations 413 are useful for visualizing and analyzing current, previous, and possible future states of assets 430, 440 connected to an operating system 410 over a network 450.
• Fig. 5 is a method diagram illustrating key steps in the communication between cyber- physical assets 430, 440 and remote servers running a business operating system 410, according to a preferred aspect.
• Any relevant sensors or sensing equipment and software must be installed on the asset 510 first, before relevant data can be sent to a business operating system 410.
• Such sensors may include a variety of implementations, including temperature sensors, GPS tracking software, accelerometers, or any other sensors and accompanying hardware and software as needed or desired by the user upon implementation of this system.
• the cyber-physical asset 430, 440 will maintain, as part of their software involvement in the system, a private key, and the requisite software for a crypto-ledger 421 implementation 520 using blockchain technology.
• Blockchain technology is essentially a method for secure message sending between network connected devices, often used for the purposes of transaction ledgers and smart contracts, using asymmetric encryption.
• the cyber physical asset will be in communication with a business operating system 410 either continuously or at set intervals 530, depending on individual implementations, according to a preferred aspect.
• the asset will, using the asymmetric encryption in blockchain crypto ledgers, send status updates based on any sensors inst alled on the asset 530.
• a business operating system that receives these updates will then verify them with previous status updates in databases 540 to ensure that the updates received are legitimate, and not forged or from a dubious source.
• the ledger held in at least one database is not updated 560. If they are properly verified and indicate they are from the real asset and indicate a legitimate status update, any databases which hold a copy of the crypto-ledger 421 are updated with the new status of the asset 550. It will be apparent to one skilled in the art that additional uses for an update verification process may be that partial updates (for example, with certain pieces of data not sent to the server in the status update) may be used, and with this partial observability, missing' data between status updates may be inferred using machine learning techniques. It is possible to implement a rules engine for this purpose, to determine what rules to apply for inference of missing data, depending on the implementation of the system.
• Fig. 6 is a method diagram illustrating key steps in a business operating system 410 interacting with data received from cyber-physical assets 430, 440 in databases 420 to verify updates in a cryptographic ledger 421, according to a preferred aspect
• Any asset must generate a public and private key 610 in accordance with the specifications of asymmetric encryption, which are known technologies in the art.
• An asset must prepare an update 620, which may mean formatting data received from any installed sensors, performing any relevant calculations or modifications to raw data, and preparing any network devices for sending the data across a network 450.
• the cyber-physical asset 430, 440 must sign any update with its private key 630, which encrypts the update in a way that only the private or public keys can be used to decrypt.
• the asset when connected to a network 450, may send the prepared and encrypted update to any "nodes 7 ' or computer systems running a business operating system 410, to be verified before being added onto the ledger 421, 640.
• Any nodes running a business operating system 410 will attempt to verify the asset status update 650, before then verifying with the ledger held in at least one database 420 and any other relevant nodes or computer systems with such a business operating system 410 that the asset update is legitimate, valid, and shall be added to the ledger of status updates from the asset 660. It is possible to implement this system and method in an ongoing identification and authentication service, for continuous updates, rather than discrete authentication and verification for discrete updates.
• Fig. 7 is a method diagram illustrating several steps in the use of smart contracts combined with cyber-physical assets, according to a preferred aspect
• Such smart contracts are possible as a result of implementing blockchain technology to not only keep track of and verify entries in crypto-ledgers 421, but to store and execute distributed programs, for the purposes of self-enforcing contracts, known as smart contracts.
• a smart contract is implemented with a domain specific language (DSL) which may be provided by a vendor of the system or specified by a user of the system 710.
• DSL domain specific language
• a DSL may be thought of as a custom programming language, and may, depending on the implementation, also be an otherwise unmodified implementation of a programming language, according to a preferred aspect.
• Conditions for smart contracts in this system may be based on the past, present, or future status of cyber-physical assets monitored by the system 720.
• the contract program executes, which may perform any number of tasks that may be programmed into a computer, including withdrawal of funds, depositing of funds, messages sent across a network 450, or other similar results of an executed program 730, according to a preferred aspect.
• These pai-ametrically-triggered remuneration contracts may be versatile and diverse in their implementation according to die needs of the consumer.
• Fig. 8 is a method diagram illustrating key steps in the function of a parametric evaluation engine 412, according to a preferred aspect
• a parametric evaluation engine 412 may query at least one database 420 ibr a ledger 421 containing previous or current status updates of at least one cyber-physical asset 430, 440, 810. This query may be performed across a network 450 from a business operating system 410 mn on a computer system and may take the form of any database query format, including NOSQLTM databases such as MONGODBTM, or SQLTM databases including MICROSOFT SQL SERVERTM and
• Asset status histories may be returnee] to a parametric evaluation engine 412, which may be listed to a user of the engine, in a basic user interlace which allows the listing and searching of such asset status update histories 820.
• Asset statuses may be viewed over time as a history rather than listed separately, if desired, for the purpose of noting and examining trends in an asset's status 830, according to an aspect
• the techniques disclosed herein may be implemented on hardware or a combination of software and hardware. For example, they may be implemented in an operating system kernel, in a separate user process, in a library package bound into network applications, on a specially constructed machine, on an application specific integrated circuit ("ASIC"), or on a network interlace card.
• ASIC application specific integrated circuit
• Software/hardware hybrid implementations of at least some of the aspects disclosed herein may be implemented on a programmable network-resident machine (which should be understood to include intermittently connected network-aware machines) selectively activated or reconfigured by a computer program stored in memory.
• Such network devices may have multiple network interfaces that may be configured or designed to utilize different types of network communication protocols.
• a general architecture for some of these machines may be described herein in order to illustrate one or more exemplar)' means by which a given unit of functionality may be implemented.
• At least some of the features or functionalities of the various aspects disclosed herein may be implemented on one or more general-purpose computers associated with one or more networks, such as for example an end-user computer system, a client computer, a network server or other server system, a mobile computing device (e.g., tablet computing device, mobile phone, smartphone, laptop, or other appropriate computing device), a consumer electronic device, a music player, or any other suitable electronic device, router, switch, or other suitable device, or any combination thereof.
• at least some of the features or functionalities of the various aspects disclosed herein may be implemented in one or more virtualized computing environments (e.g., network computing clouds, virtual machines hosted on one or more physical computing machines, or other appropriate virtual environments).
• FIG. 9 there is shown a block diagram depicting an exemplary computing device 10 suitable for implementing at least a portion of the features or functionalities disclosed herein.
• Computing device 10 may be, for example, any one of the computing machines listed in the previous paragraph, or indeed any other electronic device capable of executing software or hardware- based instructions according to one or more programs stored in memory.
• Computing device 10 may be configured to communicate with a plurality of other computing devices, such as clients or servers, over communications networks such as a wide area network a metropolitan area network, a local area network, a wireless network, the Internet, or any other network, using known protocols for such conununication, whether wireless or wired.
• communications networks such as a wide area network a metropolitan area network, a local area network, a wireless network, the Internet, or any other network, using known protocols for such conununication, whether wireless or wired.
• computing device 10 includes one or more central processing units (CPU) 12, one or more interfaces 15, and one or more busses 14 (such as a peripheral component interconnect (PCI) bus).
• CPU 12 may be responsible for implementing specific functions associated with the functions of a specifically configured computing device or machine.
• a computing' device 10 may be configured or designed to function as a server system utilizing CPU 12, local memory 11 and/or remote memory 16, and interface(s) 15.
• CPU 12 may be caused to perform one or more of the different types of functions and/or operations under the control of software modules or components, which for example, may include an operating system and any appropriate applications software, drivers, and the like.
• CPU 12 may include one or more processors 13 such as, for example, a processor from one of the Intel, ARM, Qualcomm, and AMD families of microprocessors.
• processors 13 may include specially designed hardware such as application- specific integrated circuits (ASICs), electrically erasable programmable read-only memories (EEPROMs), field programmable gate arrays (FPGAs), and so forth, for controlling operations of computing' device 10.
• ASICs application- specific integrated circuits
• EEPROMs electrically erasable programmable read-only memories
• FPGAs field programmable gate arrays
• a local memory 11 such as non-volatile random access memory (RAM) and/or read-only memory (ROM), including for example one or more levels of cached memory
• RAM non-volatile random access memory
• ROM read-only memory
• Memory 11 may be used for a variety of purposes such as, for example, caching and/or storing data, programming instructions, and the like. It should be further appreciated that CPU 12 may be one of a variety of sysiem-on-a-chip (SOC) type hardware that may include additional hardware such as memory or graphics processing chips, such as a QUALCOMM
• processor is not limited merely to those integrated circuits referred to in the art as a processor, a mobile processor, or a microprocessor, but broadly refers to a microcontroller, a microcomputer, a programmable logic controller, an application-specific integrated circuit, and any other programmable circuit
• interfaces 15 are provided as network interface cards (NICs).
• NICs control the sending and receiving of data packets over a computer network; other types of interfaces 15 may for example support other peripherals used with computing device 10.
• the interfaces that may be provided are Ethernet interfaces, frame relay interfaces, cable interfaces, DSL interfaces, token ring interfaces, graphics interfaces, and the like.
• interfaces may be provided such as, for example, universal serial bus (USB), Serial, Ethernet, FIREWIRETM, TIRINDERBOLTTM, PCI, parallel, radio frequency (RF), BLUETOOTHTM, near-field communications (e.g., using near-field magnetics), 802.11 (WiFi), frame relay, TCP/IP, ISDN, fast Ethernet interfaces, Gigabit Ethernet interfaces, Serial ATA (SATA) or external SATA (ESATA) interfaces, high- definition multimedia interface (HDMI), digital visual interface (DV1), analog or digital audio interfaces, asynchronous transfer mode (AIM) interfaces, high-speed serial interface (HSS1) interfaces. Point of Sale (POS) interfaces, fiber data distributed interfaces (FDDIs), and the like.
• USB universal serial bus
• Serial, Ethernet FIREWIRETM
• TIRINDERBOLTTM TIRINDERBOLTTM
• PCI parallel, radio frequency (RF), BLUETOOTHTM
• near-field communications e.g., using near
• RAM volatile and/or non -volatile memory
• FIG. 9 illustrates one specific architecture for a computing device 10 for implementing one or more of the inventions described herein, it is by no means the only device architecture on which at least a portion of the features and techniques described herein may be implemented.
• architectures having one or any number of processors 13 may be used, and such processors 13 may be present in a single device or distributed among any number of devices.
• a single processor 13 handles communications as well as routing computations, while in other embodiments a separate dedicated communications processor may be provided.
• different types of features or functionalities may be implemented in a system according to the invention that includes a client device (such as a tablet device or smartphone running client software) and server systems (such as a server system described in more detail below).
• the system of the present invention may employ one or more memories or memory modules (such as, for example, remote memory block 16 and local memory 11) configured to store data, program instructions for the general- purpose network operations, or other information relating to the functionality of the embodiments described herein (or any combinations of the above).
• Program instructions may control execution of or comprise an operating system and/or one or more applications, for example.
• Memory 16 or memories 11, 16 may also be configured to store data structures, configuration data, encryption data, historical system operations information, or any other specific or generic non-program information described herein.
• nontransitory machine-readable storage media may include, but are not limited to, magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD- ROM disks; magneto- optical media such as optical disks, and hardware devices that are specially configured to store and perform program instructions, such as read-only memory devices (ROM), flash memory (as is common in mobile devices and integrated systems), solid state drives (SSD) and "hybrid SSD” storage drives that may combine physical components of solid state and hard disk drives in a single hardware device (as are becoming increasingly common in the art with regard to personal computers), memristor memory, random access memory (RAM), and die like.
• ROM read-only memory
• flash memory as is common in mobile devices and integrated systems
• SSD solid state drives
• hybrid SSD hybrid SSD
• such storage means may be integral and nonremovable (such as RAM hardware modules that may be soldered onto a motherboard or otherwise integrated into an electronic device), or they may be removable such as swappable flash memory- modules (such as “thumb drives” or other removable media designed for rapidly exchanging physical storage devices), "hot swappable” hard disk drives or solid state drives, removable optical storage discs, or other such removable media, and that such integral and removable storage media may be utilized interchangeably.
• swappable flash memory- modules such as “thumb drives” or other removable media designed for rapidly exchanging physical storage devices
• hot swappable hard disk drives or solid state drives
• removable optical storage discs or other such removable media
• program instructions include both object code, such as may be produced by a compiler, machine code, such as may be produced by an assembler or a linker, byte code, such as may be generated by for example a JAVATM compiler and may be executed using a Java virtual machine or equivalent, or files containing higher level code that may be executed by the computer using an interpreter (for example, scripts written in Python, Perl, Ruby, Groovy, or any other scripting language).
• interpreter for example, scripts written in Python, Perl, Ruby, Groovy, or any other scripting language.
• systems according to the present invention may be implemented on a standalone computing system.
• FIG. 10 there is shown a block diagram depicting a typical exemplary architecture of one or more embodiments or components thereof on a standalone computing system.
• Computing' device 20 includes processors 21 that may run software that carry out one or more functions or applications of embodiments of the invention, such as for example a client application 24.
• Processors 21 may carry out computing instructions under control of an operating system 22 such as, for example, a version of MICROSOFT WINDOWSTM operating system, APPLE OSXTM or iOSTM operating systems, some variety of the Linux operating system, ANDROIDTM operating system, or the like.
• an operating system 22 such as, for example, a version of MICROSOFT WINDOWSTM operating system, APPLE OSXTM or iOSTM operating systems, some variety of the Linux operating system, ANDROIDTM operating system, or the like.
• one or more shared services 23 may be operable in system 20, and may be useful for providing common services to client applications 24.
• Services 23 may for example be WINDOWSTM services, user-space common services in a Linux environment, or any other type of common service architecture used with operating system 21.
• Input devices 28 may be of any type suitable for receiving user input, including for example a keyboard, touchscreen, microphone (for example, for voice input), mouse, touchpad, trackball, or any combination thereof.
• Output devices 27 may be of any type suitable for providing output to one or more users, whether remote or local to system 20, and may include for example one or more screens for visual output, speakers, printers, or any combination thereof.
• Memory 25 may be random-access memory having any structure and architecture known in the art, for use by processors 21, for example to run software.
• Storage devices 26 may be any magnetic, optical, mechanical, memristor, or electrical storage device for storage of data in digital form (such as those described above, referring to Fig. 9).
• Examples of storage devices 26 include flash memory, magnetic hard drive, CD-ROM, and/or the like.
• systems of the present invention may be implemented on a distributed computing network, such as one having any number of clients and/or servers.
• a distributed computing network such as one having any number of clients and/or servers.
• FIG. 11 there is shown a block diagram depicting an exemplary architecture 30 for implementing at least a portion of a system according to an embodiment of the invention on a distributed computing network.
• any number of clients 33 may be provided.
• Each client 33 may run software for implementing client-side portions of the present invention; clients may comprise a system 20 such as that illustrated in Fig. 10.
• any number of servers 32 may be provided for handling requests received from one or more clients 33.
• Clients 33 and servers 32 may communicate with one another via one or more electronic networks 31, which may be in various embodiments any of the Internet, a wide area network, a mobile telephony network (such as CDMA or GSM cellular networks), a wireless network (such as WiFi, WiMAX, LTE, and so forth), or a local area network (or indeed any network topology known in the art; the invention does not prefer any one network topology over any other).
• Networks 31 may be implemented using any known network protocols, including for example wired and/or wireless protocols.
• servers 32 may call external services 37 when needed to obtain additional information, or to refer to additional data concerning a particular call Communications with external services 37 may take place, for example, via one or more networks 31.
• external services 37 may comprise web-enabled services or functionality related to or installed on the hardware device itself.
• client applications 24 may obtain information stored in a server system 32 in the cloud or on an external service 37 deployed on one or more of a particular enterprise's or user's premises.
• clients 33 or servers 32 may make use of one or more specialized services or appliances that may be deployed locally or remotely across one or more networks 31.
• one or more databases 34 may be used or referred to by one or more embodiments of the invention. It should be understood by one having ordinary skill in the art that databases 34 may be arranged in a wide variety of architectures and using a wide variety of data access and manipulation means.
• one or more databases 34 may comprise a relational database system using a structured query language (SQL), while others may comprise an alternative data storage technology such as those referred to in die art as "NoSQL” (for example, HADOOP CASSANDRATM, GOOGLE BIGTABLETM, and so forth).
• SQL structured query language
• NoSQL alternative data storage technology
• variant database architectures such as column-oriented databases, in memory databases, clustered databases, distributed databases, or even flat file data repositories may be used according to the invention. It will be appreciated by one having ordinary skill in the art tiiat any combination of known or future database technologies may be used as appropriate, unless a specific database technology or a specific arrangement of components is specified for a particular embodiment herein. Moreover, it should be appreciated that the term "database” as used herein may refer to a physical database machine, a cluster of machines acting as a single database system, or a logical database within an overall database management system.
• Fig. 12 shows an exemplary overview of a computer system 40 as may be used in any of the various locations throughout the system. It is exemplary of any computer that may execute code to process data.
• Central processor unit (CPU ⁇ 41 is connected to bus 42, to which bus is also connected memory 43, nonvolatile memory 44, display 47, input/output (I/O) unit 48, and network interface card (NIC) 53.
• I/O unit 48 may, typically, be connected to keyboard 49, pointing device 50, hard disk 52, and real-rime clock 51.
• NIC 53 connects to network 54, which may be the Internet or a local network, which local network may or inay not have connections to the Internet.
• power supply unit 45 connected, in this example, to a main alternating current (AC) supply 46.
• AC main alternating current

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• 2019
  • 2019-02-25 EP EP19758282.8A patent/EP3756108A4/de not_active Withdrawn
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