CN117234798A - Enterprise-level data backup and recovery method and system for electric power field - Google Patents
Enterprise-level data backup and recovery method and system for electric power field Download PDFInfo
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Abstract
The invention relates to the technical field of information management, and discloses an enterprise-level data backup and recovery method and system for the electric power field, wherein the method comprises the following steps: data blocking is carried out on the power enterprise data, and encryption is carried out on the power enterprise blocking data; distributing cloud backup storage nodes to the power enterprise block encrypted data, and carrying out data backup on the power enterprise block encrypted data according to the cloud backup storage nodes and the hybrid backup mode; calculating the recovery cost of the cloud backup power enterprise data, and generating a target recovery cost function of the power enterprise data according to the recovery cost and the cost constraint function; calculating the optimal recovery cost of the target recovery cost function, and determining the recovery priority of the cloud backup power enterprise data according to the optimal recovery cost; and decrypting the cloud backup power enterprise data according to the recovery priority, and recovering the power enterprise block data into the power enterprise data. The invention can improve the accuracy of enterprise data backup and recovery.
Description
Technical Field
The invention relates to the technical field of information management, in particular to an enterprise-level data backup and recovery method and system for the electric power field.
Background
The electric power industry is a national post type industry, the power supply level and the safety condition of the electric power industry are directly related to the development of enterprises and the daily life of people, the electric power business is various and complex, the data is various and huge, and the requirement on the safety of the data is high. However, in order to improve the timely recovery of the power enterprise data in the case of an abnormal situation, an efficient data backup recovery strategy is required to be adopted for data backup recovery.
In the prior art, the data backup and recovery technology stores service data through a main data center, and a backup data center stores backup data, and when data faults occur, data is recovered from the backup data center. In practical application, when abnormal conditions occur in the main data center and the backup data center, data cannot be recovered, and consistency and integrity of the data cannot be effectively verified when the backup data center is used for recovering the data, so that accuracy in the process of carrying out enterprise-level data backup recovery is low.
Disclosure of Invention
The invention provides an enterprise-level data backup and recovery method and system for the power field, and mainly aims to solve the problem of low accuracy in the process of performing enterprise-level data backup and recovery.
In order to achieve the above purpose, the invention provides an enterprise-level data backup and recovery method for the electric power field, which comprises the following steps:
acquiring power enterprise data, performing data blocking on the power enterprise data to obtain power enterprise blocking data, and encrypting the power enterprise blocking data through a preset double encryption algorithm to obtain power enterprise blocking encrypted data;
a preset bidirectional consensus mechanism algorithm is utilized to distribute preset cloud backup storage nodes to the power enterprise block encrypted data, and the data backup is carried out on the power enterprise block encrypted data according to the cloud backup storage nodes and a preset hybrid backup mode to obtain cloud backup power enterprise data;
calculating the recovery cost of the cloud backup power enterprise data through a preset dissimilarity recovery cost algorithm, and generating a target recovery cost function of the power enterprise data according to the recovery cost and a preset cost constraint function, wherein the target recovery cost function is as follows:
；
wherein,the cost function is restored for the target,as a function of the minimum value of the function,as a function of the maximum value,as a logarithmic function,for the purpose of the recovery cost,for the penalty term coefficient, For the penalty term index,is the constraint function;
calculating the optimal recovery cost of the target recovery cost function by using a preset particle swarm optimization algorithm, and determining the recovery priority of the cloud backup power enterprise data according to the optimal recovery cost;
and decrypting the cloud backup power enterprise data according to the recovery priority through a preset double inverse encryption algorithm to obtain power enterprise block data, and recovering the power enterprise block data into the power enterprise data according to a preset hybrid recovery mode.
The step of performing data blocking on the power enterprise data to obtain power enterprise blocking data comprises the following steps:
classifying the power enterprise data according to preset power data characteristics to obtain power enterprise class data;
adding a block tag to the power enterprise class data to obtain a power enterprise data tag;
and according to a preset block index, performing data blocking on the power enterprise data according to the power enterprise data tag to obtain power enterprise blocking data.
Encrypting the power enterprise block data through a preset double encryption algorithm to obtain power enterprise block encrypted data, wherein the method comprises the following steps:
Calculating first encrypted block data of the power enterprise block data by using the double encryption algorithm, wherein the double encryption algorithm is as follows:
；
wherein,is the firstFirst encrypted block data of the individual power enterprise block data,as a function of the encryption,is the firstThe block data of the individual power enterprises,the method comprises the steps of marking the blocking data of the power enterprise;
generating the power enterprise block encryption data according to a preset encryption key and the first encryption block data, wherein the power enterprise block encryption data has a calculation formula as follows:
；
wherein,is the firstPower enterprise block encryption data of individual power enterprise block data,as a result of the encryption key,is the firstFirst encrypted block data of the individual power enterprise block data.
The distributing the preset cloud backup storage node to the block encrypted data of the power enterprise by using a preset bidirectional consensus mechanism algorithm comprises the following steps:
acquiring backup storage nodes of a cloud, and determining storage node weights of the backup storage nodes by using a preset hierarchical weight model;
ordering the backup storage nodes corresponding to the storage node weights according to the order from large to small to obtain a backup storage node queue;
Generating an electric power encryption data queue by partitioning the encryption data of the electric power enterprise;
and carrying out bidirectional consensus on the backup storage node queue and the electric power encryption data queue by using the bidirectional consensus mechanism algorithm to obtain the cloud backup storage node corresponding to the electric power enterprise block encryption data.
The bidirectional consensus algorithm is used for carrying out bidirectional consensus on the backup storage node queue and the power encryption data queue to obtain cloud backup storage nodes corresponding to the power enterprise block encryption data, and the cloud backup storage nodes comprise:
forward consensus is carried out on the storage nodes in the backup storage node queue and the encrypted data in the electric power encrypted data queue one by one to obtain a forward consensus value;
carrying out reverse consensus on the encrypted data in the electric power encrypted data queue and the storage nodes in the backup storage node queue one by one to obtain a reverse consensus value;
calculating a bidirectional consensus value of the storage node according to the forward consensus value and the reverse consensus value by using a bidirectional consensus mechanism algorithm as follows:
；
wherein,is the firstThe bi-directional consensus value of the individual storage nodes,is the firstThe storage node weights of the individual storage nodes, Is the firstThe forward consensus value of the individual storage nodes,is the firstReverse consensus values of the individual encrypted data nodes;
and selecting the storage node with the maximum bidirectional consensus value as a cloud backup storage node corresponding to the power enterprise block encryption data.
The step of carrying out data backup on the electric power enterprise block encryption data according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup electric power enterprise data comprises the following steps:
determining a backup strategy in the hybrid backup mode according to a preset backup stage;
and backing up the power enterprise block encryption data to the cloud backup storage node according to the backup strategy to obtain cloud backup power enterprise data.
The calculating the recovery cost of the cloud backup power enterprise data through a preset dissimilarisation recovery cost algorithm includes:
extracting backup attributes, storage attributes and communication attributes of the cloud backup power enterprise data;
calculating the recovery cost of the cloud backup power enterprise data according to the backup attribute, the storage attribute and the communication attribute by using the dissimilation recovery cost algorithm, wherein the dissimilation recovery cost algorithm is as follows:
；
wherein, For the purpose of the recovery cost,as a cost control factor for the cost of the device,to the first of the storage attributesThe storage cost corresponding to the individual cloud backup power enterprise data,is the firstThe cloud backs up the data volume corresponding to the power enterprise data,for the number of backups in the backup property,is the first of the communication attributesThe unit communication cost corresponding to the individual cloud backup power enterprise data,the amount of power enterprise data is backed up for the cloud.
The decrypting the cloud backup power enterprise data according to the restoration priority through a preset double inverse encryption algorithm to obtain power enterprise block data comprises the following steps:
generating a priority decryption queue of the cloud backup enterprise data according to the recovery priority in the order from big to small;
decrypting the priority decryption queue to obtain first decryption block data, wherein the calculation formula of the first decryption block data is as follows:
；
wherein,decrypting queues for the priorityIn column numberSaid first decrypted block data of individual power enterprise block data,for decrypting keys toIs used to decrypt the data of the data stream,is the firstPower enterprise block encryption data of individual power enterprise block data,the method comprises the steps of marking the blocking data of the power enterprise;
Generating a double decryption key of the cloud backup enterprise data according to the first decryption block data and the power enterprise block encrypted data;
decrypting the cloud backup power enterprise data according to the double decryption key by a preset double inverse encryption algorithm to obtain power enterprise block data, wherein the double inverse encryption algorithm is as follows:
；
wherein,is the firstThe block data of the individual power enterprises,is the firstPower enterprise blocking adding of individual power enterprise blocking dataThe data of the secret is stored,for the identification of the power enterprise blocking data,for double decryption keysIs provided.
The recovering the power enterprise block data into the power enterprise data according to a preset hybrid recovery mode includes:
determining a recovery strategy in the mixed recovery mode according to a preset block sequence;
carrying out data recovery on the power enterprise partitioned data one by one according to the recovery strategy to obtain initial power enterprise recovery partitioned data;
splicing the initial power enterprise recovery block data to obtain initial power enterprise recovery data;
and carrying out integrity check on the initial power enterprise recovery data to obtain the power enterprise data.
In order to solve the above problems, the present invention further provides an enterprise-level data backup and restore system for the power domain, the system comprising:
the power enterprise data encryption module is used for acquiring power enterprise data, carrying out data blocking on the power enterprise data to obtain power enterprise blocking data, and encrypting the power enterprise blocking data through a preset double encryption algorithm to obtain power enterprise blocking encrypted data;
the data backup module is used for distributing a preset cloud backup storage node to the power enterprise block encrypted data by utilizing a preset bidirectional consensus mechanism algorithm, and carrying out data backup on the power enterprise block encrypted data according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup power enterprise data;
the target recovery cost function generation module is used for calculating the recovery cost of the cloud backup power enterprise data through a preset dissimilarity recovery cost algorithm and generating a target recovery cost function of the power enterprise data according to the recovery cost and a preset cost constraint function;
the recovery priority determining module is used for calculating the optimal recovery cost of the target recovery cost function by using a preset particle swarm optimization algorithm, and determining the recovery priority of the cloud backup power enterprise data according to the optimal recovery cost;
And the power enterprise data recovery module is used for decrypting the cloud backup power enterprise data according to the recovery priority through a preset double inverse encryption algorithm to obtain power enterprise block data, and recovering the power enterprise block data into the power enterprise data according to a preset mixed recovery mode.
According to the embodiment of the invention, the data of the power enterprise is partitioned, so that the locality of the data can be better utilized, and the delay of data access is reduced; the data encryption is carried out on the power enterprise block data, so that malicious invasion behavior in the process of data transmission backup of the power enterprise is prevented; the cloud backup storage nodes are distributed for the block encrypted data of the power enterprise, and the data backup is carried out according to the cloud backup storage nodes, so that the backup of the data of the power enterprise is realized, the reliability of the data backup is ensured, and the backup strategy can be managed, the backup state can be monitored and the recovery operation can be carried out through the cloud control console; the recovery cost of the power enterprise data is calculated, the recovery priority is determined according to the optimal value of the recovery cost, the backup power enterprise data is decrypted according to the recovery priority, efficient data recovery can be achieved on the premise that data safety is guaranteed, risks of data loss and service interruption are reduced, further, data recovery is conducted on the power enterprise block data according to a recovery strategy, and accuracy of data recovery is improved. Therefore, the enterprise-level data backup and recovery method and system for the electric power field can solve the problem of lower accuracy in the process of performing enterprise-level data backup and recovery.
Drawings
FIG. 1 is a schematic flow chart of an enterprise-level data backup and restoration method for an electric power domain according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a cloud backup storage node allocation method according to an embodiment of the present application;
FIG. 3 is a flowchart illustrating a method for calculating recovery costs according to an embodiment of the present application;
fig. 4 is a functional block diagram of an enterprise-level data backup and restoration system for an electric power domain according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application provides an enterprise-level data backup and recovery method oriented to the power field. The execution main body of the enterprise-level data backup and recovery method facing the electric power field comprises at least one of electronic equipment, such as a server side, a terminal and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the enterprise-level data backup and restoration method facing the power domain may be executed by software or hardware installed in a terminal device or a server device, where the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of an enterprise-level data backup and restore method for an electric power domain according to an embodiment of the invention is shown. In this embodiment, the enterprise-level data backup and restoration method facing the power domain includes:
s1, acquiring power enterprise data, performing data blocking on the power enterprise data to obtain power enterprise blocking data, and encrypting the power enterprise blocking data through a preset double encryption algorithm to obtain power enterprise blocking encrypted data.
In the embodiment of the invention, the power enterprise data includes power production data, power consumption data, energy market data, equipment operation and maintenance data, supply chain data, customer management data and marketing and financial data, wherein the power enterprise data can be acquired from a pre-stored storage area through computer sentences (such as Java sentences, python sentences and the like) with a data grabbing function, and the storage area includes but is not limited to a database and a blockchain.
Further, in order to improve backup efficiency of the power enterprise data, the power enterprise data needs to be partitioned, so that locality of the data can be better utilized, and delay of data access is reduced.
In the embodiment of the invention, the partitioning data of the power enterprise refers to dividing a large-scale data set of the power enterprise according to a certain rule or logic, and dividing the data into a plurality of smaller blocks so as to effectively process, store and manage the data.
In the embodiment of the present invention, the performing data partitioning on the power enterprise data to obtain power enterprise partitioned data includes:
classifying the power enterprise data according to preset power data characteristics to obtain power enterprise class data;
adding a block tag to the power enterprise class data to obtain a power enterprise data tag;
and according to a preset block index, performing data blocking on the power enterprise data according to the power enterprise data tag to obtain power enterprise blocking data.
In detail, the power data characteristics are the basis for classifying the power enterprise data, including production and supply characteristics, power consumption characteristics, equipment state characteristics, environment and energy efficiency characteristics, market and transaction characteristics and the like, classifying the power enterprise data according to different power data characteristics, so as to obtain power enterprise class data, adding class block labels to the same type of power enterprise class data, obtaining power enterprise data labels, and performing data block according to the pre-established data block indexes and different power enterprise data labels to obtain power enterprise block data.
Further, the power enterprise data can be segmented and encrypted on the local or endpoint device, the security of the data in the transmission and storage processes can be ensured by the power enterprise segmented data, part or all of the encrypted data blocks can be backed up to a preset cloud backup storage node, and then the cloud backup storage node can be located on a server of a cloud service provider to provide extensible and safe data storage service.
In the embodiment of the invention, the block encryption data of the power enterprise refers to data encryption of the block data of the power enterprise, so that malicious intrusion behavior is prevented in the process of data transmission and backup of the power enterprise.
In the embodiment of the present invention, the encrypting the power enterprise block data by a preset double encryption algorithm to obtain power enterprise block encrypted data includes:
calculating first encrypted block data of the power enterprise block data by using the double encryption algorithm, wherein the double encryption algorithm is as follows:
；
wherein,is the firstFirst encrypted block data of the individual power enterprise block data,as a function of the encryption,is the firstThe block data of the individual power enterprises,the method comprises the steps of marking the blocking data of the power enterprise;
Generating the power enterprise block encryption data according to a preset encryption key and the first encryption block data, wherein the power enterprise block encryption data has a calculation formula as follows:
；
wherein,is the firstPower enterprise block encryption data of individual power enterprise block data,as a result of the encryption key,is the firstFirst encrypted block data of the individual power enterprise block data.
In detail, the encryption function in the dual encryption algorithm is a symmetric encryption algorithm, firstly, the serial number identifier corresponding to each piece of power enterprise block data is encrypted, then the exclusive-or calculation is carried out on the encrypted serial number identifier and the data sequence represented by the piece of power enterprise block data, the exclusive-or calculation is carried out on the encrypted serial number identifier and the original serial number identifier according to the result after the exclusive-or calculation, the encryption function is used for encryption, so that the first re-encryption of the piece of power enterprise block data is realized, the exclusive-or calculation is carried out on the encryption key generated by the symmetric encryption algorithm and the first encrypted piece of data, the piece of power enterprise block encrypted data corresponding to the piece of power enterprise block data can be obtained, the dual encryption of the piece of power enterprise block data is realized, and the security of data encryption can be improved.
Further, after the data encryption is performed on the power enterprise block data, cloud storage nodes corresponding to each power enterprise block data are distributed to each power enterprise block data, and the power enterprise data backup is realized according to the cloud storage nodes.
And S2, distributing a preset cloud backup storage node to the power enterprise block encrypted data by using a preset bidirectional consensus mechanism algorithm, and carrying out data backup on the power enterprise block encrypted data according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup power enterprise data.
In the embodiment of the invention, the power enterprises may need to perform backup storage at a plurality of geographic positions or data centers, the distribution of the data storage nodes in the distributed cloud environment can be ensured by utilizing the bidirectional consensus, and the bidirectional consensus can prevent malicious nodes from operating the data distribution process, so that the safety of data distribution is improved.
In the embodiment of the present invention, referring to fig. 2, the distributing a preset cloud backup storage node to the block encrypted data of the power enterprise by using a preset bidirectional consensus mechanism algorithm includes:
s21, acquiring backup storage nodes of the cloud, and determining storage node weights of the backup storage nodes by using a preset hierarchical weight model;
s22, sorting the backup storage nodes corresponding to the storage node weights according to the sequence from large to small to obtain a backup storage node queue;
S23, generating an electric power encryption data queue from the electric power enterprise block encryption data;
and S24, performing bidirectional consensus on the backup storage node queue and the power encryption data queue by using the bidirectional consensus mechanism algorithm to obtain the cloud backup storage node corresponding to the power enterprise block encryption data.
In detail, the backup storage nodes are storage containers created in the cloud platform and are used for storing backup data of the power enterprise data, and storage node weights of each backup storage node are determined one by one, wherein a hierarchical weight model is utilized to generate a hierarchical matrix based on availability, storage capacity, processing capacity, storage performance and the like of the backup storage nodes, and further the weights of each backup storage node are calculated according to the hierarchical matrix, and factor weights can be multiplied or weighted and summed to obtain comprehensive weights of the backup storage nodes. In addition, the factor weights in the weight model can be adjusted periodically or according to events according to the changes of service demands and conditions so as to ensure the rationality of the weights of the backup storage nodes.
Specifically, the backup storage nodes are ordered according to the calculated node weights, so that the nodes with higher weights are determined to be suitable for bearing more storage and backup tasks, a backup storage node queue is obtained, each power enterprise block encryption data is randomly generated into a power encryption data queue, and further the backup storage node queue and the power encryption data queue are subjected to bidirectional consensus through bidirectional consensus, so that the reliability of cloud backup storage node allocation is determined to be improved.
In the embodiment of the present invention, the bidirectional consensus algorithm is used to perform bidirectional consensus on the backup storage node queue and the power encryption data queue to obtain a cloud backup storage node corresponding to the power enterprise block encryption data, where the cloud backup storage node includes:
forward consensus is carried out on the storage nodes in the backup storage node queue and the encrypted data in the electric power encrypted data queue one by one to obtain a forward consensus value;
carrying out reverse consensus on the encrypted data in the electric power encrypted data queue and the storage nodes in the backup storage node queue one by one to obtain a reverse consensus value;
calculating a bidirectional consensus value of the storage node according to the forward consensus value and the reverse consensus value by using a bidirectional consensus mechanism algorithm as follows:
；
wherein,is the firstThe bi-directional consensus value of the individual storage nodes,is the firstThe storage node weights of the individual storage nodes,is the firstThe forward consensus value of the individual storage nodes,is the firstReverse consensus values of the individual encrypted data nodes;
and selecting the storage node with the maximum bidirectional consensus value as a cloud backup storage node corresponding to the power enterprise block encryption data.
In detail, the forward consensus value refers to a consensus value obtained by forward consensus of the storage nodes in the backup storage node queue with each block of encrypted data nodes in the power encrypted data queue one by one with the storage nodes in the backup storage node queue as a forward direction, and similarly, the reverse consensus value refers to a consensus value obtained by reverse consensus of each block of encrypted data in the power encrypted data queue with each block of encrypted data in the power encrypted data queue as a direction; wherein, the goal of the BFT algorithm is to enable the system to agree among the distributed nodes in the presence of at most f Byzantine faults by means of a Byzantine fault tolerance algorithm (Byzantine Fault Tolerance, BFT), even if some nodes may be malicious or abnormal, the agreement is achieved by means of a majority rule, i.e. more than half of the nodes need to agree to make decisions, the forward consensus value being the vote value obtained for each storage node by means of the Byzantine fault tolerance algorithm; the reverse consensus value refers to a vote value of each encrypted data node obtained through a Bayesian fault tolerance algorithm.
Specifically, the forward consensus value and the reverse consensus value are averaged through the bidirectional consensus mechanism algorithm to obtain a bidirectional consensus value between each storage node and each encrypted data node, wherein the storage node weight in the bidirectional consensus mechanism algorithmEach storage node can be evaluated more accurately to obtain a more accurate bidirectional consensus value, so that a better cloud backup storage node is selected, the data backup efficiency is improved, and the storage node with the largest bidirectional consensus value is selected to store the block encrypted data of the power enterprise.
For example, if the backup storage node queue includes a storage node 1, a storage node 2, and a storage node 3, and the power encryption data queue includes an encryption data node 1, an encryption data node 2, and an encryption data node 3, the storage node 1 is identified with the encryption data node 1, the encryption data node 2, and the encryption data node 3 one by one, and if the vote value obtained by the storage node 1 is 2, the forward consensus value of the storage node 1 is 2; similarly, the encrypted data node 1 is subjected to consensus with the storage node 1, the storage node 2 and the storage node 3 one by one, if the vote value obtained by the encrypted data node 1 is 1, the reverse consensus value of the storage node 1 is 1, and then the bidirectional consensus value between each storage node and each encrypted data node is calculated through a bidirectional consensus mechanism algorithm, namely the bidirectional consensus value between the storage node 1 and each encrypted data node is calculated one by one, the storage node with the largest bidirectional consensus value is selected as the cloud backup storage node corresponding to the block encrypted data of the power enterprise, and the storage node 1 is used as the cloud backup storage node of the encrypted data node 2 if the bidirectional consensus value between the storage node 1 and the encrypted data node 2 is the largest.
Further, each encrypted data is distributed to obtain a corresponding storage node, and then the encrypted data of the power enterprise is backed up to the storage node according to a backup mode, so that the backup of the data of the power enterprise is realized, the reliability of the data backup is ensured, and the backup strategy, the monitoring backup state and the recovery operation can be managed in a centralized manner through the cloud console.
In the embodiment of the invention, the cloud backup of the power enterprise data means that the power enterprise data is backed up and stored through a cloud to ensure that the data can be quickly recovered under the conditions of data loss, hardware faults, catastrophic events and the like, thereby ensuring the continuity of power business and the safety of the data.
In the embodiment of the present invention, the data backup is performed on the block encrypted data of the power enterprise according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup power enterprise data, including:
determining a backup strategy in the hybrid backup mode according to a preset backup stage;
and backing up the power enterprise block encryption data to the cloud backup storage node according to the backup strategy to obtain cloud backup power enterprise data.
In detail, the hybrid backup mode includes a full backup and an incremental backup, different backup strategies can be selected in different backup stages, and the full backup is a process of backing up all data, which is usually executed in an initial backup stage, so that the backed up data can be ensured to be complete and have no omission. However, since full backup involves backing up all data, which may require a longer time and a larger memory space, incremental backups only backup data that has been newly added or changed since the last full backup may significantly reduce the memory space and time required for the backup, which is typically faster than full backups, with full backups being performed on a periodic (possibly weekly or monthly) basis to ensure the data integrity of the backup. Namely, the backup strategy is to select full backup in the initial backup stage and incremental backup in the subsequent backup stage.
Specifically, each piece of electric power enterprise block encryption data is stored in a corresponding cloud backup storage node according to the backup strategy, so that cloud backup electric power enterprise data is obtained, cloud backup is carried out on the electric power enterprise block encryption data according to a hybrid backup mode, higher data protection, recovery capacity and usability can be provided, and meanwhile, backup management and cost burden are reduced.
Further, after the backup of the power enterprise data, when the original data of the power enterprise is damaged, the backup power enterprise data needs to be restored to obtain the complete power enterprise data, so that the decision maker needs to find the most economical and effective restoration scheme by calculating the restoration cost, thereby optimizing the utilization of resources.
And S3, calculating the recovery cost of the cloud backup power enterprise data through a preset dissimilarity recovery cost algorithm, and generating a target recovery cost function of the power enterprise data according to the recovery cost and a preset cost constraint function.
In the embodiment of the invention, when the data of the power enterprise is recovered, the cost of events and cost for recovering the data is considered, so that the consumption cost is minimum, the recovery cost comprises two costs of storage and communication, and the recovery cost of the data of the cloud backup power enterprise is determined through the storage cost and the recovery cost.
In the embodiment of the present invention, referring to fig. 3, the calculating, by a preset dissimilarity recovery cost algorithm, the recovery cost of the cloud backup power enterprise data includes:
s31, extracting backup attributes, storage attributes and communication attributes of the cloud backup power enterprise data;
s32, calculating the recovery cost of the cloud backup power enterprise data according to the backup attribute, the storage attribute and the communication attribute by utilizing the dissimilation recovery cost algorithm, wherein the dissimilation recovery cost algorithm is as follows:
；
wherein,for the purpose of the recovery cost,as a cost control factor for the cost of the device,to the first of the storage attributesThe storage cost corresponding to the individual cloud backup power enterprise data,is the firstThe cloud backs up the data volume corresponding to the power enterprise data,for the number of backups in the backup property,is the first of the communication attributesThe unit communication cost corresponding to the individual cloud backup power enterprise data,the amount of power enterprise data is backed up for the cloud.
In detail, the backup attribute refers to the number of backup data of the power enterprise data, the storage attribute refers to the number of storage nodes and the storage capacity of the power enterprise data, the communication attribute refers to the communication bandwidth and the unit communication cost of the data to be recovered, and the backup attribute, the storage attribute and the communication attribute of the cloud backup power enterprise data can be extracted through a computer sentence (such as a Java sentence) with a data grabbing function.
Specifically, the dissimilarity recovery cost algorithm refers to jointly calculating recovery cost of cloud backup power enterprise data through different dissimilarity attributes, wherein cost control factors in the dissimilarity recovery cost algorithm are various factors influencing recovery operation cost, the cost control factors can be set in a self-defined mode, the recovery difficulty in the data recovery process is small, the cost control factors can be set to be 0.1, the recovery difficulty in the data recovery process is very large, the cost control factors can be set to be 100 so as to reflect different recovery difficulties, and more sufficient preparation is provided for the recovery process and selection of recovery strategies.
Further, in order to minimize the recovery cost, it is necessary to generate a target recovery cost function, calculate the minimum cost of the target recovery cost function, and improve the data recovery efficiency.
In the embodiment of the invention, the target recovery cost function is a mathematical function for optimizing a recovery strategy, and different recovery parameters and decisions are mapped to a value representing cost. By adjusting the parameters of the recovery strategy, an economic and efficient recovery scheme can be found using the target recovery cost function to achieve a predetermined cost goal. The cost constraint function means that the sum of the data amounts of the power data recovery is smaller than the maximum storage capacity of the storage node.
In the embodiment of the present invention, the target recovery cost function of the power enterprise data is generated according to the recovery cost and a preset cost constraint function, where the target recovery cost function is:
；
wherein,the cost function is restored for the target,as a function of the minimum value of the function,as a function of the maximum value,as a logarithmic function,for the purpose of the recovery cost,for the penalty term coefficient,for the penalty term index,is the constraint function.
In detail, in the target recovery cost functionIs a penalty term coefficient, controls the weight of the penalty term,representing constraintsAnd 0 takes a larger value, i.e. only if the constraint isWhen the penalty term is greater than 0, the penalty term is acted; p is an index of penalty term for adjusting the growth rate of penalty term, penalty term coefficientAnd index of penalty termThe choice of (c) should be adjusted according to the importance of the particular problem and constraints. Larger sizeThe value will more severely penalize solutions that violate constraints, while smallerThe value will impose a smaller penalty on the solution that violates the constraint, and when the optimization algorithm attempts to approach or exceed the constraint boundary, the value of the penalty term will increase, resulting in an increase in the objective function, which in turn leads toAlgorithms tend to generate solutions that satisfy constraints.
Further, by solving the target recovery cost function, an optimal value of the recovery cost parameter value can be obtained, and therefore, the target recovery cost function needs to be solved to obtain an optimal solution, so that a recovery strategy is determined according to the optimal recovery cost.
And S4, calculating the optimal recovery cost of the target recovery cost function by using a preset particle swarm optimization algorithm, and determining the recovery priority of the cloud backup power enterprise data according to the optimal recovery cost.
In the embodiment of the present invention, the particle swarm optimization algorithm is assumed to beSearching in a dimensional space comprisingAnd (3) particles. First, theIndividual particles are atThe position in dimensional space is expressed as:first, theThe best position experienced by the individual particles is noted asFlight speed of each particleThe best position for all particles to pass through in the whole particle swarm. After finding the optimal solution, the particles can update their own speed and position according to the particle update speed calculation formula.
In the embodiment of the present invention, the calculating the optimal recovery cost of the target recovery cost function by using a preset particle swarm optimization algorithm includes:
performing particle coding on the power enterprise data to obtain power enterprise data particles;
Initializing the update speed of the power enterprise data particles to obtain an initialization speed;
updating the initialization speed according to a preset particle update speed to obtain a global optimal solution of the target recovery cost function, wherein the particle update speed calculation formula is as follows:
；
wherein,representation ofTime of day (time)First iterationThe particle update rate of the power enterprise data particles is maintained,representation ofTime of day (time)First iterationThe particle update rate of the power enterprise data particles is maintained,indicating that the particle velocity updates the weight value,the first random number is represented by a first random number,a second random number is represented by a second random number,representation ofTime of day (time)First iterationThe particle update location of the power enterprise data particles,representation ofTime of day (time)First iterationThe particles of the power enterprise data particles update the optimal locations,representation ofA global optimal solution of the target recovery cost function is obtained at the moment;
and determining the optimal recovery cost according to the global optimal solution.
In detail, taking the power enterprise data as one particle, performing particle coding on the power enterprise data to obtain power enterprise data particles, initializing the initial position and the initial speed of the power enterprise data particles, setting the initial speed to 0, further respectively updating the speed and the position of each particle, stopping updating the speed and the position of each particle when the iteration number reaches the preset maximum iteration number, calculating the global optimal value and the corresponding position of the particle with the current particle group weight, converting the global optimal value and the position into the optimal target value and the corresponding solution of the target problem, determining the optimal recovery cost according to the global optimal solution, obtaining the minimum recovery cost, and further determining the recovery priority of the cloud backup power enterprise data according to the minimum recovery cost.
Specifically, the recovery priority of the cloud backup power enterprise data is determined according to the optimal recovery cost, the cloud backup power enterprise data is stored through blocks, and the recovery priority of the cloud backup power enterprise data is determined according to the optimal recovery cost corresponding to each block, so that the smaller the optimal recovery cost is, the higher the recovery priority of the cloud backup power enterprise data is.
Further, the power enterprise data with high priority is recovered first, namely, the backup power enterprise data is decrypted first, and then the data is recovered, so that the efficient data recovery can be realized on the premise of ensuring the data safety, and the risks of data loss and service interruption are reduced.
And S5, decrypting the cloud backup power enterprise data according to the recovery priority through a preset double inverse encryption algorithm to obtain power enterprise block data, and recovering the power enterprise block data into the power enterprise data according to a preset mixed recovery mode.
In the embodiment of the invention, the double inverse encryption algorithm corresponds to a double encryption algorithm, and double decryption is performed on encrypted cloud backup power enterprise data so as to ensure the security of the power enterprise data.
In the embodiment of the present invention, the decrypting the cloud backup power enterprise data according to the restoration priority by a preset double inverse encryption algorithm to obtain power enterprise block data includes:
Generating a priority decryption queue of the cloud backup enterprise data according to the recovery priority in the order from big to small;
decrypting the priority decryption queue to obtain first decryption block data, wherein the calculation formula of the first decryption block data is as follows:
；
wherein,decrypting the first of the queues for the prioritySaid first decrypted block data of individual power enterprise block data,for decrypting keys toIs used to decrypt the data of the data stream,is the firstPower enterprise block encryption data of individual power enterprise block data,the method comprises the steps of marking the blocking data of the power enterprise;
generating a double decryption key of the cloud backup enterprise data according to the first decryption block data and the power enterprise block encrypted data;
decrypting the cloud backup power enterprise data according to the double decryption key by a preset double inverse encryption algorithm to obtain power enterprise block data, wherein the double inverse encryption algorithm is as follows:
；
wherein,is the firstThe block data of the individual power enterprises,is the firstPower enterprise block encryption data of individual power enterprise block data,for the identification of the power enterprise blocking data,for double decryption keysIs provided.
In detail, generating a priority decryption queue for cloud backup enterprise data according to the size of the restoration priority, and using an encryption key asThe symmetric decryption algorithm of (1) exclusive-ors the power enterprise block encrypted data and the serial number identification to obtain first decryption block data of the power enterprise block data, and then generates a second decryption key of cloud backup enterprise data according to the first decryption block data and the power enterprise block encrypted data, namelyAnd further decrypting the cloud backup enterprise data according to the double decryption key, thereby obtaining the power enterprise blocking data.
Further, for the decrypted power enterprise block data, the power enterprise block data can be subjected to data recovery, and the mixed recovery mode can flexibly select a recovery strategy according to the priority and importance of different data blocks, so that the recovery process is optimized, important data can be recovered preferentially, and the data recovery efficiency is improved.
In the embodiment of the present invention, the recovering the power enterprise block data into the power enterprise data according to the preset hybrid recovery mode includes:
determining a recovery strategy in the mixed recovery mode according to a preset block sequence;
Carrying out data recovery on the power enterprise partitioned data one by one according to the recovery strategy to obtain initial power enterprise recovery partitioned data;
splicing the initial power enterprise recovery block data to obtain initial power enterprise recovery data;
and carrying out integrity check on the initial power enterprise recovery data to obtain the power enterprise data.
In detail, the recovery policy is determined according to different blocks, if the data is segmented according to the sequence, that is, the sequence of the blocks accords with the logic sequence of the data, continuous recovery can be performed, starting from the first block, and recovering the data one by one according to the sequence until all the blocks are recovered; if the sequence of the data blocks is random, parallel recovery can be performed while recovering a plurality of blocks, and the parallel processing capacity is utilized to accelerate the recovery speed; if the data blocks are sorted according to the priority, the blocks with high priority can be recovered first by priority recovery, so that important data can be recovered as soon as possible or asynchronously recovered, and a plurality of recovery tasks with high priority can be simultaneously carried out, and the recovery tasks with high priority can be executed in a queue, so that the important data can be recovered quickly.
Specifically, performing data recovery on the power enterprise partitioned data according to the recovery strategy to obtain initial power enterprise recovery partitioned data, and splicing each piece of recovered initial power enterprise recovery partitioned data to obtain complete initial power enterprise recovery data.
Further, to ensure that the recovered data remains consistent and intact with the original data. This helps to verify that the data is not corrupted or tampered with during the backup, transfer and recovery processes, and when the data is backed up, a hash value or checksum is calculated and recorded for each data block, and during the recovery process, the chunked data is decrypted and recovered, the hash value or checksum is recalculated for the recovered data block, and the recalculated hash value or checksum is compared with the pre-recorded value to verify the integrity of the data, so that it is ensured that the recovered data is consistent with the original data and no tampering or corruption has occurred.
According to the embodiment of the invention, the data of the power enterprise is partitioned, so that the locality of the data can be better utilized, and the delay of data access is reduced; the data encryption is carried out on the power enterprise block data, so that malicious invasion behavior in the process of data transmission backup of the power enterprise is prevented; the cloud backup storage nodes are distributed for the block encrypted data of the power enterprise, and the data backup is carried out according to the cloud backup storage nodes, so that the backup of the data of the power enterprise is realized, the reliability of the data backup is ensured, and the backup strategy can be managed, the backup state can be monitored and the recovery operation can be carried out through the cloud control console; the recovery cost of the power enterprise data is calculated, the recovery priority is determined according to the optimal value of the recovery cost, the backup power enterprise data is decrypted according to the recovery priority, efficient data recovery can be achieved on the premise that data safety is guaranteed, risks of data loss and service interruption are reduced, further, data recovery is conducted on the power enterprise block data according to a recovery strategy, and accuracy of data recovery is improved. Therefore, the enterprise-level data backup and recovery method and system for the electric power field can solve the problem of lower accuracy in the process of performing enterprise-level data backup and recovery.
Fig. 4 is a functional block diagram of an enterprise-level data backup and restore system for electric power domain according to an embodiment of the present invention.
The enterprise-level data backup and recovery system 100 oriented to the power domain can be installed in electronic equipment. Depending on the functions implemented, the enterprise-wide data backup and restoration system 100 may include a power enterprise data encryption module 101, a data backup module 102, a target restoration cost function generation module 103, a restoration priority determination module 104, and a power enterprise data restoration module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the power enterprise data encryption module 101 is configured to obtain power enterprise data, perform data blocking on the power enterprise data to obtain power enterprise blocking data, encrypt the power enterprise blocking data through a preset double encryption algorithm, and obtain power enterprise blocking encrypted data;
The data backup module 102 is configured to allocate a preset cloud backup storage node to the power enterprise block encrypted data by using a preset bidirectional consensus mechanism algorithm, and perform data backup on the power enterprise block encrypted data according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup power enterprise data;
the target recovery cost function generating module 103 is configured to calculate a recovery cost of the cloud backup power enterprise data according to a preset dissimilarity recovery cost algorithm, and generate a target recovery cost function of the power enterprise data according to the recovery cost and a preset cost constraint function;
the restoration priority determining module 104 is configured to calculate an optimal restoration cost of the target restoration cost function by using a preset particle swarm optimization algorithm, and determine a restoration priority of the cloud backup power enterprise data according to the optimal restoration cost;
the power enterprise data recovery module 105 is configured to decrypt the cloud backup power enterprise data according to the recovery priority through a preset double inverse encryption algorithm to obtain power enterprise block data, and recover the power enterprise block data into the power enterprise data according to a preset hybrid recovery mode.
In detail, each module in the power domain oriented enterprise data backup and restore system 100 in the embodiment of the present application adopts the same technical means as the power domain oriented enterprise data backup and restore method described in fig. 1 to 3, and can produce the same technical effects, which are not repeated here.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Claims (10)
1. An enterprise-level data backup and restoration method oriented to the electric power field is characterized by comprising the following steps:
acquiring power enterprise data, performing data blocking on the power enterprise data to obtain power enterprise blocking data, and encrypting the power enterprise blocking data through a preset double encryption algorithm to obtain power enterprise blocking encrypted data;
a preset bidirectional consensus mechanism algorithm is utilized to distribute preset cloud backup storage nodes to the power enterprise block encrypted data, and the data backup is carried out on the power enterprise block encrypted data according to the cloud backup storage nodes and a preset hybrid backup mode to obtain cloud backup power enterprise data;
Calculating the recovery cost of the cloud backup power enterprise data through a preset dissimilarity recovery cost algorithm, and generating a target recovery cost function of the power enterprise data according to the recovery cost and a preset cost constraint function, wherein the target recovery cost function is as follows:
；
wherein,restoring a cost function for said object, +.>As a function of the minimum value +.>As a maximum function>As a logarithmic function>For the recovery cost, < >>For penalty term coefficients, < >>For penalty index, < >>Is the constraint function;
calculating the optimal recovery cost of the target recovery cost function by using a preset particle swarm optimization algorithm, and determining the recovery priority of the cloud backup power enterprise data according to the optimal recovery cost;
and decrypting the cloud backup power enterprise data according to the recovery priority through a preset double inverse encryption algorithm to obtain power enterprise block data, and recovering the power enterprise block data into the power enterprise data according to a preset hybrid recovery mode.
2. The power domain oriented enterprise data backup and restore method of claim 1, wherein the performing data blocking on the power enterprise data to obtain power enterprise blocking data comprises:
Classifying the power enterprise data according to preset power data characteristics to obtain power enterprise class data;
adding a block tag to the power enterprise class data to obtain a power enterprise data tag;
and according to a preset block index, performing data blocking on the power enterprise data according to the power enterprise data tag to obtain power enterprise blocking data.
3. The method for recovering backup of enterprise data in the power domain according to claim 1, wherein encrypting the power enterprise block data by a preset double encryption algorithm to obtain power enterprise block encrypted data comprises:
calculating first encrypted block data of the power enterprise block data by using the double encryption algorithm, wherein the double encryption algorithm is as follows:
；
wherein,is->First encrypted block data of individual power enterprise block data,/->For encryption function->Is->Individual power enterprise block data->The method comprises the steps of marking the blocking data of the power enterprise;
generating the power enterprise block encryption data according to a preset encryption key and the first encryption block data, wherein the power enterprise block encryption data has a calculation formula as follows:
；
Wherein,is->Electric power enterprise block encryption data of individual electric power enterprise block data,/->For the encryption key, < >>Is->First encrypted block data of the individual power enterprise block data.
4. The power domain oriented enterprise data backup and restoration method as claimed in claim 1, wherein the allocating a preset cloud backup storage node to the power enterprise block encrypted data by using a preset bidirectional consensus mechanism algorithm comprises:
acquiring backup storage nodes of a cloud, and determining storage node weights of the backup storage nodes by using a preset hierarchical weight model;
ordering the backup storage nodes corresponding to the storage node weights according to the order from large to small to obtain a backup storage node queue;
generating an electric power encryption data queue by partitioning the encryption data of the electric power enterprise;
and carrying out bidirectional consensus on the backup storage node queue and the electric power encryption data queue by using the bidirectional consensus mechanism algorithm to obtain the cloud backup storage node corresponding to the electric power enterprise block encryption data.
5. The method for recovering enterprise-level data backup oriented to the power domain according to claim 4, wherein the performing bidirectional consensus on the backup storage node queue and the power encryption data queue by using the bidirectional consensus mechanism algorithm to obtain a cloud backup storage node corresponding to the power enterprise block encryption data comprises:
Forward consensus is carried out on the storage nodes in the backup storage node queue and the encrypted data in the electric power encrypted data queue one by one to obtain a forward consensus value;
carrying out reverse consensus on the encrypted data in the electric power encrypted data queue and the storage nodes in the backup storage node queue one by one to obtain a reverse consensus value;
calculating a bidirectional consensus value of the storage node according to the forward consensus value and the reverse consensus value by using a bidirectional consensus mechanism algorithm as follows:
；
wherein,is->Bidirectional consensus value of the individual storage nodes, +.>Is->Storage node weights of the individual storage nodes, +.>Is the firstForward consensus value of the individual storage nodes, respectively>Is->Reverse consensus values of the individual encrypted data nodes;
and selecting the storage node with the maximum bidirectional consensus value as a cloud backup storage node corresponding to the power enterprise block encryption data.
6. The method for recovering enterprise-level data backup for an electric power domain according to claim 1, wherein the performing data backup on the electric power enterprise block encrypted data according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup electric power enterprise data comprises:
Determining a backup strategy in the hybrid backup mode according to a preset backup stage;
and backing up the power enterprise block encryption data to the cloud backup storage node according to the backup strategy to obtain cloud backup power enterprise data.
7. The power domain oriented enterprise data backup and restoration method as claimed in claim 1, wherein the computing the restoration cost of the cloud backup power enterprise data by a preset dissimilarisation restoration cost algorithm comprises:
extracting backup attributes, storage attributes and communication attributes of the cloud backup power enterprise data;
calculating the recovery cost of the cloud backup power enterprise data according to the backup attribute, the storage attribute and the communication attribute by using the dissimilation recovery cost algorithm, wherein the dissimilation recovery cost algorithm is as follows:
；
wherein,for the recovery cost, < >>Is a cost control factor->For the +.>Storage cost corresponding to personal cloud backup power enterprise data, < >>Is->Data amount corresponding to personal cloud backup power enterprise data, < ->For the number of backups in the backup property, +.>For the +.>Unit communication cost corresponding to personal cloud backup power enterprise data, < > >The amount of power enterprise data is backed up for the cloud.
8. The power domain oriented enterprise data backup and restoration method as claimed in claim 1, wherein the decrypting the cloud backup power enterprise data according to the restoration priority by a preset double inverse encryption algorithm to obtain power enterprise block data comprises:
generating a priority decryption queue of the cloud backup enterprise data according to the recovery priority in the order from big to small;
decrypting the priority decryption queue to obtain first decryption block data, wherein the calculation formula of the first decryption block data is as follows:
；
wherein,decrypting the +.>Said first decrypted block data of individual power enterprise block data,for decryption key +.>Decryption function of->Is->Electric power enterprise block encryption data of individual electric power enterprise block data,/->The method comprises the steps of marking the blocking data of the power enterprise;
generating a double decryption key of the cloud backup enterprise data according to the first decryption block data and the power enterprise block encrypted data;
decrypting the cloud backup power enterprise data according to the double decryption key by a preset double inverse encryption algorithm to obtain power enterprise block data, wherein the double inverse encryption algorithm is as follows:
；
Wherein,is->Individual power enterprise block data->Is->Electric power enterprise block encryption data of individual electric power enterprise block data,/->Identification of block data for power enterprises, +.>For double decryption key->Is provided.
9. The power domain oriented enterprise data backup and restoration method of claim 1, wherein restoring the power enterprise block data to the power enterprise data according to a preset hybrid restoration mode comprises:
determining a recovery strategy in the mixed recovery mode according to a preset block sequence;
carrying out data recovery on the power enterprise partitioned data one by one according to the recovery strategy to obtain initial power enterprise recovery partitioned data;
splicing the initial power enterprise recovery block data to obtain initial power enterprise recovery data;
and carrying out integrity check on the initial power enterprise recovery data to obtain the power enterprise data.
10. An enterprise-wide data backup and restore system for electric power domain, for executing the enterprise-wide data backup and restore method for electric power domain according to any one of claims 1 to 9, the system comprising:
The power enterprise data encryption module is used for acquiring power enterprise data, carrying out data blocking on the power enterprise data to obtain power enterprise blocking data, and encrypting the power enterprise blocking data through a preset double encryption algorithm to obtain power enterprise blocking encrypted data;
the data backup module is used for distributing a preset cloud backup storage node to the power enterprise block encrypted data by utilizing a preset bidirectional consensus mechanism algorithm, and carrying out data backup on the power enterprise block encrypted data according to the cloud backup storage node and a preset hybrid backup mode to obtain cloud backup power enterprise data;
the target recovery cost function generation module is used for calculating the recovery cost of the cloud backup power enterprise data through a preset dissimilarity recovery cost algorithm and generating a target recovery cost function of the power enterprise data according to the recovery cost and a preset cost constraint function;
the recovery priority determining module is used for calculating the optimal recovery cost of the target recovery cost function by using a preset particle swarm optimization algorithm, and determining the recovery priority of the cloud backup power enterprise data according to the optimal recovery cost;
And the power enterprise data recovery module is used for decrypting the cloud backup power enterprise data according to the recovery priority through a preset double inverse encryption algorithm to obtain power enterprise block data, and recovering the power enterprise block data into the power enterprise data according to a preset mixed recovery mode.
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