CN118018562B - Intelligent mobile phone is stored to distributed high in clouds - Google Patents
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Abstract
The invention belongs to the field of cloud storage, relates to a data analysis technology, and aims to solve the problem that a distributed cloud storage intelligent mobile phone in the prior art cannot be combined with the network state of the intelligent mobile phone to carry out data reading mode screening; according to the method, the system and the device, the data reading modes of the user are analyzed, the network state of the mobile device of the user is analyzed, the data preview mode screening analysis is carried out according to the analysis result, different data reading modes are distributed for the terminal devices in different network states, and the cloud data reading fluency of the user is improved.
Description
Technical Field
The invention belongs to the field of cloud storage, relates to a data analysis technology, and particularly relates to a distributed cloud storage smart phone.
Background
The distributed cloud storage smart phone is a smart phone solution based on cloud computing and distributed storage technology, and is characterized in that data are stored on a plurality of nodes in a scattered mode through the distributed storage technology, so that the safety and reliability of the data are improved, the smart phone is used as client equipment to be responsible for user interaction and data display, and data of photos, videos, files and the like of a user are uploaded to the cloud and stored on the plurality of nodes in a scattered mode.
However, in the prior art, the distributed cloud storage smart phone only can store and display data in a movement way, but cannot combine with the network state of the smart phone to screen data reading modes, so that user experience cannot be guaranteed, and meanwhile, cloud data is randomly stored on the distributed nodes, so that the balance of the storage nodes and the data security are poor.
The application provides a solution to the technical problem.
Disclosure of Invention
The invention aims to provide a distributed cloud storage smart phone, which is used for solving the problem that the distributed cloud storage smart phone in the prior art cannot be used for screening a data reading mode in combination with the network state of the smart phone.
The technical problems to be solved by the invention are as follows: how to provide a distributed cloud storage smart phone which can combine the network state of the smart phone to screen data reading modes.
The aim of the invention can be achieved by the following technical scheme: the distributed cloud storage smart phone comprises a processor, wherein the processor is in communication connection with a background authentication module, a reading analysis module, a storage module and a server, and the server is in communication connection with a node management module and an uploading management module;
the background authentication module is used for identifying and authenticating the identity information of the user;
the reading analysis module is used for analyzing the data reading mode of the user: the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, when the user does not select independently, the process of carrying out data reading by adopting the offline packaging mode for the latest L1 times is marked as an offline analysis process, an offline coefficient LX of the offline analysis process is obtained, and the data reading mode is screened through the offline coefficient LX;
The node management module is used for managing the distributed storage nodes of the cloud data and marking the balance nodes;
The uploading management module is used for carrying out node screening management analysis when cloud data are uploaded and stored: when the server receives the uploaded cloud data, a screening coefficient SX of the balance node is obtained, the balance node with the smallest value of the screening coefficient SX is marked as a node to be selected, the node to be selected with the smallest value of the stored value is marked as the screening node, the cloud data uploaded by the user is stored in the screening node, and a data storage list of background information is updated.
In a preferred embodiment of the present invention, the method for performing identification and authentication on the identity information of the user includes fingerprint identification and authentication, face identification and authentication, and palm print identification and authentication, and after the identification and authentication pass, the background authentication module retrieves the background information of the user from the server and sends the background information to the processor, and the processor receives the background information and sends the background information to the viewing analysis module.
As a preferred embodiment of the present invention, the acquisition process of the offline coefficient LX of the offline analysis process includes: acquiring a downlink value, a bandwidth value and a packet loss value of an offline analysis process, wherein the downlink value is a minimum speed value of data downloading in the offline analysis process, the bandwidth value is a maximum network bandwidth value in the offline analysis process, and the packet loss value is packet loss times in the offline analysis process; summing and averaging the downlink values of all the offline analysis processes to obtain downlink data XX, summing and averaging the bandwidth values of all the offline analysis processes to obtain bandwidth data DK, and summing and averaging the packet loss values of all the offline analysis processes to obtain packet loss data DB; and obtaining an offline coefficient LX in an offline analysis process by carrying out numerical calculation on the downlink data XX, the bandwidth data DK and the packet loss data DB.
As a preferred embodiment of the present invention, the specific process of screening the data viewing mode includes: the offline threshold LXmin is obtained by the storage module, and the offline coefficient LX of the offline analysis process is compared with the offline threshold LXmin: if the offline coefficient LX is smaller than the offline threshold LXmin, determining that the offline analysis process does not have the reading priority, and performing data reading by adopting an online preview mode: performing data reading on the cloud according to the user requirements; if the offline coefficient LX is greater than or equal to the offline threshold LXmin, determining that the offline analysis process has a reading priority, and performing data reading in an offline packaging mode: and downloading the corresponding data packet from the cloud to the mobile phone terminal according to the user demand, and carrying out local reading on the mobile phone terminal by the user after decompression.
As a preferred embodiment of the present invention, a specific process for managing a distributed storage node of cloud data includes: acquiring the data storage amount of a distributed storage node of current cloud data, marking the data storage amount as a storage value of the storage node, forming a storage set by the storage values of all the storage nodes, performing variance calculation on all elements in the storage set to obtain a distribution coefficient of the storage set, and comparing the distribution coefficient with a preset distribution threshold value: if the distribution coefficient is smaller than the distribution threshold, judging that the storage balance of the distributed storage nodes of the current cloud data meets the requirement, and marking all elements in the storage set as balance nodes; if the distribution coefficient is greater than or equal to the distribution threshold, deleting the storage node with the largest storage value in the storage set, then recalculating the distribution coefficient, comparing the new distribution coefficient with the distribution threshold until the value of the distribution coefficient is smaller than the distribution threshold, and marking the balance node.
As a preferred embodiment of the present invention, the process for obtaining the screening coefficient SX of the balance node includes: acquiring background information of an uploading user, calling a memory value of a stored data packet of the corresponding user background information in a balance node, marking the memory value as a matching value of the balance node, and obtaining a matching value of the balance node according to a formulaThe screening coefficients SX, beta 1 and beta 2 of the balance node relative to the background information are proportionality coefficients, beta 1 is more than beta 2 is more than 1, and PP and CC are respectively the matching value and the storage value of the balance node.
The invention also provides a working method of the distributed cloud storage smart phone, which comprises the following steps:
Step one: identifying and authenticating identity information of a user: after the identification authentication is passed, the background authentication module invokes background information of the user from the server and sends the background information to the processor, and the processor receives the background information and then sends the background information to the reading analysis module;
Step two: analyzing the data reading mode of the user: the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, an offline coefficient LX of an offline analysis process is calculated when the user does not select independently, and the data reading mode is selected through the offline coefficient LX;
Step three: and managing the distributed storage nodes of the cloud data: acquiring the data storage amount of the distributed storage nodes of the current cloud data, marking the data storage amount as the storage values of the storage nodes, forming a storage set by the storage values of all the storage nodes, and marking the balance nodes according to the distribution coefficients of the storage set;
Step four: and (3) carrying out node screening management analysis when the cloud data are uploaded and stored: and acquiring background information of the uploading user when the server receives the uploaded cloud data, calculating a screening coefficient SX by combining the memory value and the storage value of the data packet stored in the balance node by the background information, and marking the screening node by the screening coefficient SX.
The invention has the following beneficial effects:
1. The data reading mode of the user can be analyzed through the reading analysis module, the network state of the mobile equipment of the user is analyzed, the data preview mode screening analysis is carried out according to the analysis result, different data reading modes are distributed for the terminal equipment in different network states, and the cloud data reading fluency of the user is improved;
2. The node management module can manage the distributed storage nodes of the cloud data, analyze the data storage amount of the distributed storage nodes of the cloud data and mark the storage nodes meeting the storage balance requirement, so that the balance and efficiency of the cloud data storage and calling are improved;
3. the node screening management analysis can be carried out when the cloud data is uploaded and stored through the uploading management module, the screening coefficient is obtained through comprehensive analysis and calculation by combining the stored data quantity of the nodes and the data storage quantity of the corresponding user in the balance node, the storage nodes are screened through the screening coefficient, the storage node selection rationality during each data uploading is improved, and the reduction of the data storage efficiency and the safety caused by randomly selecting the storage nodes is avoided.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
Fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: as shown in fig. 1, the distributed cloud storage smart phone comprises a processor, wherein the processor is in communication connection with a background authentication module, a reading analysis module, a storage module and a server, and the server is in communication connection with a node management module and an uploading management module.
The background authentication module is used for identifying and authenticating identity information of a user: the method for identifying and authenticating the identity information of the user comprises fingerprint identification authentication, face identification authentication and palm print identification authentication, and after the identification authentication is passed, the background authentication module retrieves background information of the user from the server and sends the background information to the processor, and the processor receives the background information and then sends the background information to the reading analysis module.
The reading analysis module is used for analyzing the data reading mode of the user: the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, when the user does not select autonomously, the latest L1 processes of data reading by adopting the offline packaging mode are marked as offline analysis processes, downlink values, bandwidth values and packet loss values of the offline analysis processes are obtained, the downlink values are the minimum speed value of data downloading in the offline analysis processes, the bandwidth values are the maximum network bandwidth values in the offline analysis processes, and the packet loss values are the packet loss times in the offline analysis processes;
summing and averaging the downlink values of all the offline analysis processes to obtain downlink data XX, summing and averaging the bandwidth values of all the offline analysis processes to obtain bandwidth data DK, and summing and averaging the packet loss values of all the offline analysis processes to obtain packet loss data DB; by the formula Obtaining an offline coefficient LX of an offline analysis process, wherein alpha 1, alpha 2 and alpha 3 are proportionality coefficients, and alpha 1 is more than alpha 2 and more than alpha 3 is more than 1;
The offline threshold LXmin is obtained by the storage module, and the offline coefficient LX of the offline analysis process is compared with the offline threshold LXmin: if the offline coefficient LX is smaller than the offline threshold LXmin, determining that the offline analysis process does not have the reading priority, and performing data reading by adopting an online preview mode: performing data reading on the cloud according to the user requirements; if the offline coefficient LX is greater than or equal to the offline threshold LXmin, determining that the offline analysis process has a reading priority, and performing data reading in an offline packaging mode: downloading the corresponding data packet from the cloud to the mobile phone terminal according to the user demand, and performing local reading on the mobile phone terminal by the user after decompression; analyzing the data reading mode of the user, analyzing the network state of the mobile device of the user, screening and analyzing the data preview mode according to the analysis result, distributing different data reading modes for terminal devices in different network states, and improving the cloud data reading fluency of the user.
The node management module is used for managing the distributed storage nodes of the cloud data: acquiring the data storage amount of a distributed storage node of current cloud data, marking the data storage amount as a storage value of the storage node, forming a storage set by the storage values of all the storage nodes, performing variance calculation on all elements in the storage set to obtain a distribution coefficient of the storage set, and comparing the distribution coefficient with a preset distribution threshold value: if the distribution coefficient is smaller than the distribution threshold, judging that the storage balance of the distributed storage nodes of the current cloud data meets the requirement, and marking all elements in the storage set as balance nodes;
If the distribution coefficient is greater than or equal to the distribution threshold, deleting the storage node with the largest storage value in the storage set, then recalculating the distribution coefficient, comparing the new distribution coefficient with the distribution threshold until the value of the distribution coefficient is smaller than the distribution threshold, and marking the balance node; the method comprises the steps of managing the distributed storage nodes of cloud data, analyzing the data storage amount of the distributed storage nodes of the cloud data, and marking the storage nodes meeting the storage balance requirement, so that the balance and efficiency of cloud data storage and calling are improved.
The uploading management module is used for carrying out node screening management analysis when the cloud data are uploaded and stored: when the server receives the uploaded cloud data, acquiring background information of an uploading user, calling a memory value of a stored data packet of the corresponding user background information in a balance node, marking the memory value as a matching value of the balance node, and obtaining a matching value of the balance node according to a formulaThe screening coefficients SX, beta 1 and beta 2 of the balance node relative to the background information are proportionality coefficients, beta 1 is more than beta 2 is more than 1, and PP and CC are respectively the matching value and the storage value of the balance node;
marking a balance node with the smallest screening coefficient SX value as a node to be selected, marking the node to be selected with the smallest storage value as a screening node, storing cloud data uploaded by a user into the screening node, and updating a data storage list of background information; and carrying out node screening management analysis when the cloud data is uploaded and stored, comprehensively analyzing and calculating the stored data quantity of the nodes and the data storage quantity of the corresponding user in the balance node to obtain screening coefficients, screening the storage nodes through the screening coefficients, improving the storage node selection rationality during each data uploading, and avoiding the reduction of data storage efficiency and safety caused by randomly selecting the storage nodes.
Embodiment two: as shown in fig. 2, the invention further provides a working method of the distributed cloud storage smart phone, which comprises the following steps:
Step one: identifying and authenticating identity information of a user: after the identification authentication is passed, the background authentication module invokes background information of the user from the server and sends the background information to the processor, and the processor receives the background information and then sends the background information to the reading analysis module;
Step two: analyzing the data reading mode of the user: the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, an offline coefficient LX of an offline analysis process is calculated when the user does not select independently, and the data reading mode is selected through the offline coefficient LX;
Step three: and managing the distributed storage nodes of the cloud data: acquiring the data storage amount of the distributed storage nodes of the current cloud data, marking the data storage amount as the storage values of the storage nodes, forming a storage set by the storage values of all the storage nodes, and marking the balance nodes according to the distribution coefficients of the storage set;
Step four: and (3) carrying out node screening management analysis when the cloud data are uploaded and stored: and acquiring background information of the uploading user when the server receives the uploaded cloud data, calculating a screening coefficient SX by combining the memory value and the storage value of the data packet stored in the balance node by the background information, and marking the screening node by the screening coefficient SX.
When the distributed cloud storage smart phone works, after identification and authentication are passed, a background authentication module retrieves background information of a user from a server and sends the background information to a processor, and the processor receives the background information and then sends the background information to a reading analysis module; the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, an offline coefficient LX of an offline analysis process is calculated when the user does not select independently, and the data reading mode is selected through the offline coefficient LX; acquiring the data storage amount of the distributed storage nodes of the current cloud data, marking the data storage amount as the storage values of the storage nodes, forming a storage set by the storage values of all the storage nodes, and marking the balance nodes according to the distribution coefficients of the storage set; and acquiring background information of the uploading user when the server receives the uploaded cloud data, calculating a screening coefficient SX by combining the memory value and the storage value of the data packet stored in the balance node by the background information, and marking the screening node by the screening coefficient SX.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: formula (VI); Collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding offline coefficient for each group of sample data; substituting the set offline coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 of 4.35, 2.63 and 2.12 respectively;
The size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding offline coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the offline coefficient is proportional to the value of the bandwidth data.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (4)
1. The distributed cloud storage intelligent mobile phone is characterized by comprising a processor, wherein the processor is in communication connection with a background authentication module, a reading analysis module, a storage module and a server, and the server is in communication connection with a node management module and an uploading management module;
the background authentication module is used for identifying and authenticating the identity information of the user;
the reading analysis module is used for analyzing the data reading mode of the user: the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, when the user does not select independently, the process of carrying out data reading by adopting the offline packaging mode for the latest L1 times is marked as an offline analysis process, an offline coefficient LX of the offline analysis process is obtained, and the data reading mode is screened through the offline coefficient LX;
The node management module is used for managing the distributed storage nodes of the cloud data and marking the balance nodes;
The uploading management module is used for carrying out node screening management analysis when cloud data are uploaded and stored: when the server receives the uploaded cloud data, acquiring a screening coefficient SX of the balance node, marking the balance node with the smallest value of the screening coefficient SX as a node to be selected, marking the node to be selected with the smallest value of the stored value as the screening node, storing the cloud data uploaded by the user into the screening node, and updating a data storage list of background information;
The obtaining process of the offline coefficient LX of the offline analysis process includes: acquiring a downlink value, a bandwidth value and a packet loss value of an offline analysis process, wherein the downlink value is a minimum speed value of data downloading in the offline analysis process, the bandwidth value is a maximum network bandwidth value in the offline analysis process, and the packet loss value is packet loss times in the offline analysis process; summing and averaging the downlink values of all the offline analysis processes to obtain downlink data XX, summing and averaging the bandwidth values of all the offline analysis processes to obtain bandwidth data DK, and summing and averaging the packet loss values of all the offline analysis processes to obtain packet loss data DB; by the formula Obtaining an offline coefficient LX of an offline analysis process, wherein alpha 1, alpha 2 and alpha 3 are proportionality coefficients, and alpha 1 is more than alpha 2 and more than alpha 3 is more than 1;
The specific process for screening the data reading mode comprises the following steps: the offline threshold LXmin is obtained by the storage module, and the offline coefficient LX of the offline analysis process is compared with the offline threshold LXmin: if the offline coefficient LX is smaller than the offline threshold LXmin, determining that the offline analysis process does not have the reading priority, and performing data reading by adopting an online preview mode: performing data reading on the cloud according to the user requirements; if the offline coefficient LX is greater than or equal to the offline threshold LXmin, determining that the offline analysis process has a reading priority, and performing data reading in an offline packaging mode: downloading the corresponding data packet from the cloud to the mobile phone terminal according to the user demand, and performing local reading on the mobile phone terminal by the user after decompression;
The specific process for managing the distributed storage nodes of the cloud data comprises the following steps: acquiring the data storage amount of a distributed storage node of current cloud data, marking the data storage amount as a storage value of the storage node, forming a storage set by the storage values of all the storage nodes, performing variance calculation on all elements in the storage set to obtain a distribution coefficient of the storage set, and comparing the distribution coefficient with a preset distribution threshold value: if the distribution coefficient is smaller than the distribution threshold, judging that the storage balance of the distributed storage nodes of the current cloud data meets the requirement, and marking all elements in the storage set as balance nodes; if the distribution coefficient is greater than or equal to the distribution threshold, deleting the storage node with the largest storage value in the storage set, then recalculating the distribution coefficient, comparing the new distribution coefficient with the distribution threshold until the value of the distribution coefficient is smaller than the distribution threshold, and marking the balance node.
2. The distributed cloud storage smart phone according to claim 1, wherein the identification and authentication method for the identity information of the user includes fingerprint identification and authentication, face identification and palm print identification and authentication, and after the identification and authentication are passed, the background authentication module retrieves background information of the user from the server and sends the background information to the processor, and the processor receives the background information and sends the background information to the browsing analysis module.
3. The distributed cloud storage smart phone of claim 2, wherein the process of obtaining the screening coefficient SX of the balance node includes: acquiring background information of an uploading user, calling a memory value of a stored data packet of the corresponding user background information in a balance node, marking the memory value as a matching value of the balance node, and obtaining a matching value of the balance node according to a formulaThe screening coefficients SX, beta 1 and beta 2 of the balance node relative to the background information are proportionality coefficients, beta 1 is more than beta 2 is more than 1, and PP and CC are respectively the matching value and the storage value of the balance node.
4. A distributed cloud storage smart phone according to any of claims 1-3, wherein the working method of the distributed cloud storage smart phone comprises the following steps:
Step one: identifying and authenticating identity information of a user: after the identification authentication is passed, the background authentication module invokes background information of the user from the server and sends the background information to the processor, and the processor receives the background information and then sends the background information to the reading analysis module;
Step two: analyzing the data reading mode of the user: the data reading mode comprises an online preview mode and an offline packaging mode, wherein the data reading mode is selected by a user independently, an offline coefficient LX of an offline analysis process is calculated when the user does not select independently, and the data reading mode is selected through the offline coefficient LX;
Step three: and managing the distributed storage nodes of the cloud data: acquiring the data storage amount of the distributed storage nodes of the current cloud data, marking the data storage amount as the storage values of the storage nodes, forming a storage set by the storage values of all the storage nodes, and marking the balance nodes according to the distribution coefficients of the storage set;
Step four: and (3) carrying out node screening management analysis when the cloud data are uploaded and stored: and acquiring background information of the uploading user when the server receives the uploaded cloud data, calculating a screening coefficient SX by combining the memory value and the storage value of the data packet stored in the balance node by the background information, and marking the screening node by the screening coefficient SX.
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