CN112738090A - Data integrity detection method based on green computing consensus mechanism block chain in edge computing - Google Patents
Data integrity detection method based on green computing consensus mechanism block chain in edge computing Download PDFInfo
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Abstract
The invention discloses a data integrity detection method based on a green computing consensus mechanism block chain in edge computing. The task node collects information of each edge node, workload certification is carried out through a green computing consensus mechanism, a block chain recorder is elected at intervals, and the recorder packs and issues user transactions to the block chain. The edge compute node verifies the validity of the newly issued block and if the block is recognized, the next time the block is added behind the block, and if the block is not recognized, the block is discarded. The edge calculation user can check own data at any time, and applies a data hash value to any edge node in the block chain so as to detect the integrity of the user data. Has the advantages of high efficiency, energy saving, safety and reliability.
Description
Technical Field
The invention relates to an edge calculation, a block chain technology and a copy integrity detection technology, in particular to a data integrity detection method based on a block chain of a green calculation consensus mechanism in the edge calculation.
Background
The edge calculation is distributed at one side close to a data source, and an open platform integrating network, calculation, storage and application is adopted to provide services nearby. The application program is initiated at the edge side to generate a faster network service response, and the infrastructure is an infrastructure capable of sharing cloud computing storage computing and access pressure. The architecture is different from cloud computing which is used for transmitting all data to a data center, and various bottlenecks of the cloud computing are avoided.
However, in the conventional edge computing, the number of edge storage devices is large, it is difficult to ensure the integrity of user data and whether the user data is illegally tampered, which brings great risk to the data owner of the edge node and also brings great challenge to the provider of the edge node.
The blockchain is a decentralized completely distributed system, and an effective consensus mechanism is needed, so that each node in the blockchain can achieve consensus, and data consistency and safety performance are guaranteed. The method integrates the knowledge of point-to-point transmission, a consensus mechanism, cryptography and distributed storage, and is a brand new application mode. The block chain technology also brings new opportunities and challenges to the internet security direction, and by utilizing the non-tamper property and the transparency of the blocks, the integrity of user data is ensured, the consensus mechanism in the blocks is improved, the data placement efficiency is improved, and the cost is saved.
Therefore, the block chain based on the green computing consensus mechanism is combined with the safety detection strategy of the edge computing storage, and an efficient, energy-saving, safe and reliable edge computing network can be created.
Disclosure of Invention
The invention aims to solve the problem that data integrity is difficult to detect in edge calculation, and provides a data integrity detection method based on a green calculation consensus mechanism block chain in edge calculation. And the bookkeeper adds the integrity check evidence of the file to the block chain, and extracts the evidence from the block chain when the integrity of the file needs to be detected, so that the integrity of the file can be verified. The resource waste of the block chain is reduced, and the consensus efficiency of the block chain and the safety of the files in the edge nodes are improved.
In view of the above, the technical scheme adopted by the invention is as follows: the data integrity detection method based on the green computing consensus mechanism block chain in the edge computing comprises the following steps:
(1) the edge computing device receives the data stored by the edge computing user, and dynamically stores the data in the appropriate edge computing node through a scheduling algorithm.
(2) The task node collects information of each edge node, workload certification is carried out through a green computing consensus mechanism, a block chain recorder is elected at intervals, and the recorder packs and issues user transactions to the block chain.
(3) The edge compute node verifies the validity of the newly issued block and if the block is recognized, the next time the block is added behind the block, and if the block is not recognized, the block is discarded.
(4) The edge calculation user can check own data at any time, and applies a data hash value to any edge node in the block chain so as to detect the integrity of the user data.
The invention has the following advantages:
the invention combines the block chain which is not completely decentralized with the block chain, manages the placement information of the copy in the edge node, and utilizes the property that the block chain can not be tampered to store the summary information of the copy, thereby ensuring the integrity of the copy in the next access. And by using the distributed characteristic of the block chain, each user can check the integrity of the copy at any time, the placement information can not be easily tampered, and the third party is not required to be used for verification. And finally, protecting the privacy of the user and the data security by using the anonymity of the block chain. The edge nodes in the invention achieve consensus by using a green calculation work evidence consensus mechanism, and the work evidence has the characteristics of difficult counterfeiting, low collision, easy verification, high efficiency, green calculation and the like. When the self-operation is proved, useless calculation is not done at all, but meaningful decisions are made, and the bookkeeper is elected according to the quality of the decisions. Therefore, useless calculation can be greatly reduced, and the common knowledge with other nodes is achieved.
Drawings
FIG. 1 is a flow chart of a block chain data integrity detection method based on a green computing consensus mechanism according to a preferred embodiment of the present invention;
FIG. 2 is a block diagram of a block chain data integrity detection method based on green computing consensus mechanism according to a preferred embodiment of the present invention;
FIG. 3 is a block diagram of transactions and blocks in a block chain based on a green-colored computation consensus mechanism;
FIG. 4 is a diagram of steps taken when a user intends to query for file integrity.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments, and the objects and effects of the present invention will become more apparent, and the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a data integrity detection method based on a green computing consensus mechanism block chain in edge computing, aiming at the problem that data integrity is difficult to detect in edge computing, the method combines the block chain with the edge computing, does not use a work certification consensus mechanism, uses part of saved computing resources for computing file deployment positions, achieves consensus among nodes through advantages and disadvantages of the deployment positions, and elects a block chain bookkeeper. And the bookkeeper adds the integrity check evidence of the file to the block chain, and extracts the evidence from the block chain when the integrity of the file needs to be detected, so that the integrity of the file can be verified. The resource waste of the block chain is reduced, and the consensus efficiency of the block chain and the safety of the files in the edge nodes are improved.
With reference to fig. 1 and 2, the method of the present invention specifically comprises the following steps:
(1) the edge computing device receives the data stored by the edge computing user, and dynamically stores the data in the appropriate edge computing node through a scheduling algorithm.
(2) The task node collects information of each edge node, workload certification is carried out through a green computing consensus mechanism, a block chain recorder is elected at intervals, and the recorder packs and issues user transactions to the block chain.
(3) The edge compute node verifies the validity of the newly issued block and if the block is recognized, the next time the block is added behind the block, and if the block is not recognized, the block is discarded.
(4) The edge calculation user can check own data at any time and apply a data hash value to any edge node in the block chain so as to detect the integrity of the user data.
Specifically, in the embodiment of the present invention, the members in the blockchain are: the system comprises Edge Nodes (EN), Temporary Storage Nodes (TSN), Task Nodes (TN) and User Nodes (UN). The EN is mainly responsible for storing user data and elects a blockchain recorder through a green computing consensus mechanism; the TSN is responsible for storing user information before a deployment result comes out; the TN packages the data size and quantity stored by all users in a period of time and the edge node information of all participating in the election of the blockchain recorder into tasks, sends the tasks to all ENs, the ENs execute a data placement algorithm after receiving the information, the same parameters are used for solving the problem of file placement, different placement results generated by each EN are used as the basis of work certification, and then the blockchain recorder is elected according to the work certification. The recorder packs the user data information collected by the task scheduling node in the period of time into a block and adds the block to the current block chain.
In the step (1), data are dynamically stored in a proper edge computing node through a scheduling algorithm, and a placement result is computed through a built-in dynamic placement algorithm of each EN and a Task issued by a TN.
Referring to fig. 3, the green computing consensus mechanism steps include:
(1) a task information collection period, wherein the TSN collects data to be placed, temporarily stores the data in the node and simultaneously collects data information
The signal is sent to the TN,
information indicating the ith file in the temporary storage node TSN, i is 1, …, m, and m indicates that there are m files in total in the TSN. TN collects current each edge node state information
Indicating the status information of the ith edge nodefileAnd InodePacking into one task T ═ (I)file,Inode)。
(2) And (4) placing the task to be issued, and issuing T to each EN by the TN.
(3) A placement result calculation period, each EN using the same task T, calculates a placement result Ri，RiAnd representing the calculation result of the ith node, returning the calculation result to the TN by the EN after the calculation is finished, and not knowing the calculation result between the edge nodes EN before the TN publishes the calculation result. Wait for EN to calculate TimecalculationNot fixed, but with a maximum threshold, in general
Timecalculation iRepresents the calculation Time, of the placement result of the ith nodethresholdIndicating a set maximum wait threshold time, when this time is reached, no longer waiting for the next phase to be entered;
(4) in the election period of the bookkeeper, the task scheduling node publishes the placement result and ranks R (R)1,R2,R3...Ri) All edge nodes EN verify the ranking by placing the result RiWhether the corresponding evaluation index E can be obtainedi，V(Ri,Ei) Indicating whether verification can be performed from R by using the placement result and the evaluation indexiIs calculated to obtain Ei. Individual nodes verify ranking onlyThe first result, validation, is by voting its calculator. If the verification fails, the verification is suboptimal, and so on. And selecting the node with the most votes for recording people for the block chain of the round.
(5) The most voted placement method is used as the actual placement method, and the user data is placed using this method. The placement method refers to that each file is placed on different edge nodes, and how to place the files is to comprehensively consider factors such as file sizes and node performances, so that a better placement result is calculated. The placing method can generate a placing evaluation standard, placing time or resource amount consumed by placing can be used as evaluation of the quality of a placing result in an actual scene, and all placing methods can be ranked and voted in step 3 by adopting any evaluation mode.
(6) Data are strictly placed according to the placement result, a user can know the placement condition of the data and package the placement information of the data into a transaction T, wherein the T comprises: user public Key KeypData Placement location URLfileHash (T). And performing hash operation on the transaction to obtain a hash (T), and signing the sig (the hash (T) by using an asymmetric encryption algorithmk) And packaging and sending to a bookkeeper S ((T)k,sig(hash(Tk))),Nedge)。
(7) The bookkeeper receives the affairs of each user and packs the affairs into a BlockbodySequentially calculating the root value Merkel root of a plurality of transactions, and then taking a hash, hash (Block) of the Block bodybody) And sign (hash) the hash valuebody) Plus Block header Block)headThe complete block is constructed. The bookkeeper adds the blocks into the blockchain, broadcasts the new blockchain, honest nodes verify that the signature acknowledges the verified blocks, and honest nodes only add blocks behind the longest blockchain.
Further, as shown in fig. 4, the user intends to detect the integrity of the data of the user, and can send a detection application to any edge node, and the edge node only needs to transmit the hash value of the data corresponding to the user, so that the user can calculate the value of the Merkel root by himself, and can know whether the data is complete or not by comparison.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and although the invention has been described in detail with reference to the foregoing examples, it will be apparent to those skilled in the art that various changes in the form and details of the embodiments may be made and equivalents may be substituted for elements thereof. All modifications, equivalents and the like which come within the spirit and principle of the invention are intended to be included within the scope of the invention.
Claims (6)
1. The data integrity detection method based on the green computing consensus mechanism block chain in the edge computing is characterized by comprising the following steps of:
(1) the edge computing equipment receives data stored by an edge computing user, and dynamically stores the data in a proper edge computing node through a scheduling algorithm;
(2) the task node collects information of each edge node, the workload is proved through a green computing consensus mechanism, a block chain recorder is elected at intervals, and the recorder packs and issues user transactions to the block chain;
(3) the edge computing node verifies the validity of the newly issued block, if the block is identified, the block is continuously added behind the block next time, and if the block is not identified, the block is discarded;
(4) the edge calculation user can check own data at any time, and applies a data hash value to any edge node in the block chain so as to detect the integrity of the user data.
2. The method for detecting data integrity in edge computing based on block chain of green computing consensus mechanism as claimed in claim 1, wherein: the members in the block chain comprise an edge node EN, a temporary storage node TSN, a task node TN and a user node UN, wherein the EN is responsible for storing user data and elects a block chain recorder through a green computing consensus mechanism; the TSN is responsible for storing user information before a deployment result comes out; the TN packs the data size and quantity stored by all users in a period of time and the edge node information of all users participating in the election of the blockchain recorder into tasks, sends the tasks to all ENs, the ENs perform a data placement algorithm after receiving the information, the same parameters are used for solving the problem of file placement, different placement results generated by each EN are used as the basis of work proofs, then the work proofs show that the user data information collected by task scheduling nodes in the period of time is packed into blocks by the recorders, and the blocks are added to the current blockchain.
3. The method for detecting data integrity in edge computing based on block chain of green computing consensus mechanism as claimed in claim 2, wherein: the green computing consensus mechanism comprises the following steps:
1) in the task information collection period, the TSN collects data to be placed, temporarily stores the data in the node and simultaneously collects data information
The signal is sent to the TN,
information i indicating the ith file in the temporary storage node TSN is 1, …, m, m indicates that there are m files in the TSN in total, TN collects the current state information of each edge node
Indicating the status information of the ith edge nodefileAnd InodePacking into a Task (I)file,Inode)；
2) Placing the tasks to be issued, and issuing the tasks T to each EN by the TN;
3) the placement result calculation period, each EN using the same Task, calculates the placement result Ri，RiRepresenting the calculation result of the ith node, and returning the calculation result to the TN by the EN after the calculation is finished;
4) in the election period of the bookkeeper, the task node publishes the placement result and ranks R (R)1,R2,R3...Ri) Verifying the ranking by all edge nodes, wherein each edge node only verifies the first ranking result, votes the calculator by verification, and verifies whether the result is suboptimal if the result cannot pass verification, and so on, and selects the node with the most votes as the block chain bookkeeper in the round;
5) using the placement method with the most votes as the actual placement method, and placing the user data by using the method;
6) the user packs the placement information of the data of the user into a transaction T, wherein the T comprises: user public Key KeypData Placement location URLfileAnd performing a hash operation on the transaction, hash (T), signing the hash value sig (hash (T) using an asymmetric cryptographic algorithmk) And packaging and sending to a bookkeeper S ((T)k,sig(hash(Tk))),Nedge)；
7) The bookkeeper receives the affairs of each user and packs the affairs into a BlockbodySequentially calculating the root value Merkel root of a plurality of transactions, and then taking a hash, hash (Block) of the Block bodybody) And sign (hash) the hash valuebody) Plus Block header Block)headForming a complete block, adding the block into a block chain by a bookkeeper, and broadcasting a new block chain.
4. The method for detecting data integrity in edge computing based on block chain of green computing consensus mechanism as claimed in claim 3, wherein: before the TN publishes the operation result in the step 3), the nodes do not know the operation result mutually, and the EN waits for calculating the TimecalculationWith the maximum value of the threshold value being present,
Timecalculation irepresents the calculation Time, of the placement result of the ith nodethresholdIndicating a set maximum wait threshold time that is reached before waiting for the next phase.
5. The method for detecting data integrity in edge computing based on block chain of green computing consensus mechanism as claimed in claim 3, wherein: the verification method in the step 4) is to place a result RiWhether the corresponding evaluation index E can be obtainediThus, verification is performed, V (R)i,Ei) Indicating whether verification can be performed from R by using the placement result and the evaluation indexiIs calculated to obtain Ei。
6. The method for detecting data integrity in edge computing based on block chain of green computing consensus mechanism as claimed in claim 1, wherein: and (4) the integrity of the user data is detected, wherein the user sends a detection application to any edge node, the edge node transmits a hash value of the data corresponding to the user, the user calculates the root value of the Mercker tree by himself, and whether the data is complete or not can be obtained through comparison.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113726758A (en) * | 2021-08-25 | 2021-11-30 | 百保(上海)科技有限公司 | Data privacy calculation method and system based on block chain |
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