CN116366669A - Consensus method based on reputation value weight balance suitable for crowdsourcing system - Google Patents
Consensus method based on reputation value weight balance suitable for crowdsourcing system Download PDFInfo
- Publication number
- CN116366669A CN116366669A CN202310350174.XA CN202310350174A CN116366669A CN 116366669 A CN116366669 A CN 116366669A CN 202310350174 A CN202310350174 A CN 202310350174A CN 116366669 A CN116366669 A CN 116366669A
- Authority
- CN
- China
- Prior art keywords
- node
- consensus
- nodes
- transaction
- account management
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000000694 effects Effects 0.000 claims abstract description 63
- 238000012795 verification Methods 0.000 claims abstract description 43
- 238000012856 packing Methods 0.000 claims abstract description 8
- 238000011156 evaluation Methods 0.000 claims description 52
- 238000004364 calculation method Methods 0.000 claims description 19
- 238000012790 confirmation Methods 0.000 claims description 15
- 230000007246 mechanism Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 6
- 230000001960 triggered effect Effects 0.000 claims description 6
- 230000009471 action Effects 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 230000000977 initiatory effect Effects 0.000 claims description 3
- 230000005284 excitation Effects 0.000 abstract description 4
- 238000007726 management method Methods 0.000 description 46
- 238000004891 communication Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 238000013461 design Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 206010033799 Paralysis Diseases 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 102100037009 Filaggrin-2 Human genes 0.000 description 1
- 101000878281 Homo sapiens Filaggrin-2 Proteins 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000001976 improved effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012858 packaging process Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000012358 sourcing Methods 0.000 description 1
- 230000004936 stimulating effect Effects 0.000 description 1
- 238000010200 validation analysis Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/104—Peer-to-peer [P2P] networks
- H04L67/1042—Peer-to-peer [P2P] networks using topology management mechanisms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/104—Peer-to-peer [P2P] networks
- H04L67/1044—Group management mechanisms
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/104—Peer-to-peer [P2P] networks
- H04L67/1061—Peer-to-peer [P2P] networks using node-based peer discovery mechanisms
- H04L67/1065—Discovery involving distributed pre-established resource-based relationships among peers, e.g. based on distributed hash tables [DHT]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/40—Network security protocols
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- Computer Security & Cryptography (AREA)
- Accounting & Taxation (AREA)
- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Finance (AREA)
- Databases & Information Systems (AREA)
- Strategic Management (AREA)
- Data Mining & Analysis (AREA)
- Computer Hardware Design (AREA)
- Marketing (AREA)
- Technology Law (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Mathematical Physics (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention discloses a consensus method based on credit value weight balancing, which is applicable to a crowdsourcing system, wherein a mixed block chain architecture is adopted to divide a block chain network into an open network and a consensus network; the common node in the open network engages in transaction activities, only has reference rights to the information on the blockchain, and is divided into a service provider and a consumer according to the supply and demand relationship of the service; and the account management node of the consensus network is responsible for updating and maintaining the blockchain, and is divided into a verifier responsible for transaction verification and block verification and a leader responsible for block packing and block updating according to the reputation value model. The consensus protocol mainly completes one consensus activity through four steps, namely acquisition of a consensus list, verification of a transaction group, verification of a block and excitation and punishment. The consensus protocol provided by the invention is applied to a crowdsourcing system, and can well solve the single-point fault problem and the unfair problem faced by the traditional crowdsourcing.
Description
Technical Field
The invention belongs to the field of blockchains, and relates to a consensus method based on reputation value weight balance, which is applicable to a crowdsourcing system.
Background
Crowd sourcing is a new business model that makes the internet service industry viable. People can seek services or provide services through the crowdsourcing platform, and the timeliness of internet communication enables such demands and offerings to quickly establish contact. However, conventional crowdsourcing applications are generally built on a centralized structure, which makes the crowdsourcing system limited to conventional central architecture while developing, and mainly appears in two aspects: firstly, the problem of single-point failure is that the data of a crowdsourcing platform user depends on a centralized database, and once a server is paralyzed or attacked, the user cannot use crowdsourcing service on one hand, and the privacy of the user can be revealed on the other hand; second, fairness, when disputes are generated between the service provider and the consumer, all rely on subjective arbitration schemes given by the crowdsourcing platform, if arbitration is biased towards the consumer, the consumer can use this mechanism to steal the originality of the service provider without paying, if arbitration is biased towards the service provider, the service provider can obtain rewards without providing service or with providing a lower service. The block chain technology solves the problems faced by the traditional crowdsourcing platform, deploys crowdsourcing application on the block chain, changes a centralized architecture into a distributed architecture, and can well solve the problem of service paralysis caused by single-point faults and solve the problem of unfairness caused by centralization.
In the existing research, the measures of applying the block linking technology to the crowdsourcing system at the consensus layer are mainly divided into 2 types:
is prepared from PoofTrust [1] The representative protocol is characterized in that the selection right of the transaction and the right of packing the transaction into blocks are divided and executed by different roles, the protocol uses a designed trust value model to calculate the trust value of each node so as to distinguish different roles, the node with the highest trust value is usually a Leader, and is mainly responsible for packing the blocks, the rest is a verifier, and is mainly responsible for verifying the transaction and verifying the blocks. However, this protocol gives the option and validation of the transaction to nodes in the open network without any incentive and penalty measures to restrict such nodes participating in the consensus, which can easily lead to privacy leakage involved in the transaction.
Another by zkCrowd [2] The zkCrowd is a representative double-chain structure technology, and comprises a public chain and a private chain, user sensitive information is stored on the private chain, a block is generated by adopting a PBFT consensus protocol, and then the block is uploaded to the public chain in a zero knowledge proof mode, and the public chain confirms the transaction involved in the new block by adopting a traditional consensus method. The privacy disclosure problem of the user is reduced by the private chain and the small-range consensus node, but in the specific implementation process of the double-chain structure, when the processed transaction is bigger, the time consumption for generating one block is longer, and the real-time performance required by the crowdsourcing system cannot be well met.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a common identification method based on reputation value split weight balance, which is applicable to a crowdsourcing system. Nodes in the open network engage in transaction activities, and only have reference rights to information on the blockchain, and the nodes are called ordinary nodes; the nodes of the consensus network are responsible for updating and maintaining blockchains, and such nodes are called ledger administration nodes. The open network is divided into two roles of service provider and consumer according to the supply and demand relationship of the service. The account book management node of the consensus network divides two roles according to the reputation value model, one is a verifier responsible for transaction verification and block verification, and the other is a leader responsible for block packing and block updating.
The implementation of the consensus method based on reputation weighted balance in the present invention uses a consensus mechanism based on reputation weighted balance, and the implementation process of the consensus method includes (in the following explanation of the consensus mechanism, unless otherwise specified, the indicated nodes represent only ledger administration nodes, and the verifier and verifier nodes, leader and leader nodes refer to the same object respectively):
step one: each account management node collects relevant data including the account management nodes related to credit value calculation;
step two: calculating the credit values of all account management nodes according to the credit value model to obtain a current consensus node list comprising all account management nodes, wherein the node with the highest credit value is a leader node, and the rest nodes are verifier nodes; the reputation value model refers to a calculation method of comprehensive multiple-aspect reputation values, and is used for calculating a final reputation value model;
step three: the verifier node selects a group of transactions from the transaction pool, and sends the transactions to the leader node after verification is successful;
step four: the leader packs the successfully verified transaction to generate a new block, and broadcasts the new block to the verifier node for verification;
step five: the leader updates the successfully verified block to the blockchain, completes one consensus activity, and resets the protocol state.
The invention provides a consensus method based on credit value weight balance suitable for a crowdsourcing system, which comprises the following steps: deposit D paid by node, incentive I obtained by consensus activity by node, service evaluation table FBscore obtained by common node as service provider provider ＝{fb 1 ,fb 2 ,…fb m Common node as consumer-acquired consumer lineTo evaluate Table FbScare consumer ＝{fb 1 ,fb 2 ,…fb m The number of successes m and the number of failures n that the node has already generated to participate in the consensus activity (if a new block is successfully generated, it is considered as a successful number, otherwise it is a failed number). The service evaluation table is generated in such a way that a service provider receives service evaluation from a consumer after the service is completed, and all service evaluation obtained by transaction form a service evaluation table; the service evaluation means that a transaction is completed, and the consumer scores the provided services of the service provider from 0 to k, namely, the service evaluation table FBScare provider Is a rating score fb of (2) m E 0 … k. Similarly, after the consumer completes the transaction and evaluates the service, the service provider will score the consumer behavior from 0 to k, and the consumer behavior evaluation scores of all transactions form a consumer behavior evaluation table, i.e., FBScore consumer 。
The invention provides a consensus method based on credit value weight balance suitable for a crowdsourcing system, wherein in the second step, the step of generating a consensus node list comprises the following steps:
step 2.1: and each account management node calculates the credit values of all account management nodes including the account management node, and a consensus node list is obtained according to the arrangement of the credit values. After the list is obtained through calculation, if the reputation value of the node i is highest, the node i is used as a leader, the node i signs the list and then broadcasts the list to other account management nodes, and the other account management nodes wait for the list transmitted by the node i;
step 2.2: after receiving the list, other account management nodes compare with a list of a consensus node obtained by local calculation, if the lists are consistent, a list confirmation message is broadcast, otherwise, the list is discarded;
step 2.3: and counting list confirmation messages uploaded by the network by all account management nodes, if the number of the messages collected in the overtime time exceeds two thirds of the number of the account management nodes, considering the list to be effective, and otherwise, triggering a view switching protocol.
The view switching is a processing state when the protocol enters an exception, and mainly confirms whether the consensus cluster can reach consensus again after the exception occurs, and the list confirmation is a state that the protocol normally goes on, and the two messages are messages in different states. View switching has application in common consensus protocols such as PBFT and RAFT.
When the number of list confirmation messages does not exceed the number of account management nodes by 2/3, the view switching is triggered.
The invention provides a credit value-based weight-dividing balance consensus method suitable for a crowdsourcing system, which comprises the following steps of:
step 2.1.1: according to a financial and reputation conversion formula, calculating a reputation value of each account management node obtained by financial, mainly considering deposit paid by the node and excitation obtained through consensus activities, wherein the calculation mode is M (t) =sigmod (sigma log (D+I)), wherein sigma is a conversion factor, D is deposit paid by the node, and I is excitation obtained by the node;
step 2.1.2: according to two evaluation tables (a service evaluation table and a consumption behavior evaluation table) formed by the account management node in the transaction activity, positive feedback evaluation alpha and negative feedback evaluation beta of each node are calculated. Service evaluation table or consumption behavior evaluation table { fb ] of known node 1 ,fb 2 ,…fb m Score fb in } i ∈[1,k],i∈[1,m]If (3)
Evaluation fb of the node formed in this transaction i Is a forward evaluation, which is recorded in a set P to obtain p= { fb 1 ,fb 2 ,…fb s By calculation ∈ ->
Obtaining positive feedback evaluation alpha of current round of nodes (t) The method comprises the steps of carrying out a first treatment on the surface of the If->
Illustrating node formation at this transactionIs (f) is (b) an evaluation of fb i Is a negative evaluation, which is recorded in a set N to give n= { fb 1 ,fb 2 ,…fb m-s By calculation ∈ ->
Obtaining negative feedback evaluation beta of current round of nodes (t) . Positive feedback evaluation according to two evaluation tables>
And negative feedback evaluation->
The credit value obtained by the current round of node through transaction activity is calculated by the following calculation modes: />
Wherein k is i Feedback weights representing two evaluation tables (k is used in actual processing 1 ＝k 2 =0.5), PR is a penalty factor (PR>1)；
Step 2.1.3: according to the success and failure times of the account management node participating in the consensus activity, calculating the reputation value obtained by the node through the consensus activity in the calculation mode of
Where m is the number of success times of consensus activities that the node has participated in, n is the number of failure times of verification of the consensus activities that the node has participated in, and PR represents a penalty factor (PR)>1)；
Step 2.1.4: according to the reputation values of the three aspects generated in the steps 2.1.1-2.1.3, calculating the final reputation value of the node, wherein the calculation formula is as follows:
the reputation value of a node is more dependent on the behavior of the node in the transaction activity and in the consensus activity, so the weight should be sized to fit w 2 ＝w 3 >w 1 。
The invention provides a credit value-based weight sharing and balancing consensus method suitable for a crowdsourcing system, which comprises the following steps in step 2.3 when a view is switched to a protocol:
step 2.3.1: the account management node currently participating in the consensus activity initiates a view switching message to all account management nodes except the account management node;
step 2.3.2: and in the timeout period, after all account management nodes collect the view switching messages exceeding two thirds of the account management nodes, the current view number is increased by one, otherwise, the protocol state is reset, and the view number is restored to the default value.
The invention provides a credit value-based weight sharing balance consensus method suitable for a crowdsourcing system, which comprises the following steps of:
step 3.1: the node with the highest reputation value in the verifier (namely the node with the second reputation value rank in all account management nodes of the current round) is responsible for selecting a group of transactions from a transaction pool, and the nodes are signed and then broadcast to other verifier nodes;
step 3.2: after receiving the group of transactions, other verifier nodes check each transaction and pre-execute the transaction, wherein the pre-execute function of the transaction is to generate corresponding transaction receipts, if the generated receipts are consistent with the transaction quantity, the signature correctness of the transaction group initiating nodes and other verifiers is continuously checked in sequence, if the signature correctness is correct, the transaction group verification is successful, and transaction verification success information is sent to other verifier nodes;
step 3.3: the number of the transaction verification success messages received by the verifier node exceeds two thirds of the current consensus node list, the group of transaction verification success is indicated, the transaction verification success messages are sent to the leader node, and if the transaction verification success messages are not received within the timeout time, the view switching protocol is triggered.
The invention provides a credit value-based weight sharing balance consensus method suitable for a crowdsourcing system, wherein in the fourth step, the block verification step is as follows:
step 4.1: checking whether the signature of the block creator is correct, if not, discarding the block without broadcasting, and if so, performing the next step;
step 4.2: checking whether the signed verifier list is on a locally generated list, if not, discarding the block without broadcasting, if so, signing the block and broadcasting a block confirmation message to the network;
step 4.3: and in the timeout period, the leader checks whether enough block confirmation messages are obtained, if the number exceeds two thirds of the current consensus node list, the block verification is successful, and otherwise, the view switching protocol is triggered.
Step five, a mechanism of incentive and punishment is also included, when the leader submits the new block to the blockchain, transaction execution operation is executed at the same time, and the result of the transaction execution operation is updated to the local database; the other account management nodes download the latest block update from the leader node to the local; if the new block is successfully updated to the local, the current round of consensus activity is considered to be successful, and all nodes participating in the consensus activity acquire an incentive according to the contribution degree of participation, wherein the incentive is given in a prize pool maintained by the system; in the protocol execution process, any action causes the block to be submitted to fail, and the current round of consensus activity is considered to be failed, all nodes participating in the current round of consensus activity are punished, the punished mechanism is to collect partial deposit of the nodes, and the flow direction of the deposit is a prize pool maintained by the system.
The communication between the nodes of the present invention is based on the communication protocol of IPFS.
In the present invention, "verifier" and "verifier node", "leader" and "leader node" may be common.
The beneficial effects of the invention include: the consensus method provided by the invention adopts a ProofTrust mode, namely, the selection right of the transaction and the packing right of the block are divided, but the selection right and the verification work of the transaction are not handed to the trusted common node in the open network, but are taken charge of by the node of the consensus network in a small range, so that the problem that the privacy problem related in the transaction is exposed in the open network can be effectively reduced. According to the mixed blockchain architecture adopted by the invention, the nodes are divided into two networks, only one chain is required to be maintained, compared with a zkCrowd double-chain structure, the time consumption of generating a new zone is greatly reduced, and experimental results show that when the number of transactions needing to be packed is 1500, the time required for generating a new zone is 40.0s under the condition of the zkCrowd double-chain structure, and the consensus method provided by the invention only needs 4.5s. The invention provides a new reputation value model, which influences the reputation performance of a node by quantifying the transaction behavior of the node, and further constrains the performance of the node in consensus activities. The invention designs the incentive system and the punishment system, which not only encourages the nodes to actively participate in the consensus activities, but also prevents the node from doing bad actions.
Drawings
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 diagram of the overall architecture of a crowdsourcing system designed in accordance with the present invention.
Fig. 2 is a communication protocol diagram of an application of the present invention.
Fig. 3 is a state machine diagram of the consensus protocol of the present invention.
Fig. 4 is a schematic diagram of consensus list acquisition in accordance with the present invention.
FIG. 5 is a schematic diagram of the transaction verification of the present invention.
FIG. 6 is a schematic diagram of block verification according to the present invention.
FIG. 7 is a graph of experimental simulation results of the present invention.
FIG. 8 is a flow chart of a reputation value based weighting balancing consensus method of the present invention.
Detailed Description
The invention will be described in further detail with reference to the following specific examples and drawings. The procedures, conditions, experimental methods, etc. for carrying out the present invention are common knowledge and common knowledge in the art, except for the following specific references, and the present invention is not particularly limited.
The method adopts a mixed block chain architecture to divide a block chain network into an open network and a consensus network; the nodes in the open network engage in transaction activities, and only have reference rights to the information on the blockchain, namely common nodes, and the common nodes are divided into service providers and consumers according to the supply and demand relationship of the service; the nodes of the consensus network are responsible for updating and maintaining the blockchain, which is called an account management node, and the account management node is divided into a verifier responsible for transaction verification and block verification and a leader responsible for block packing and block updating according to a reputation value model. The consensus protocol mainly completes one consensus activity through four steps, namely acquisition of a consensus list, verification of a transaction group, verification of a block and excitation and punishment. In the invention, each round of consensus activities only generates a leader, and the blocks are generated by the leader nodes, so that the problem of block bifurcation can be avoided, and on the other hand, the verification work of the transaction and the verification work of the blocks are handed to the verifier nodes selected according to the reputation value, so that the unfair problem can be well avoided. The consensus protocol provided by the invention is applied to a crowdsourcing system, and can well solve the single-point fault problem and the unfair problem faced by the traditional crowdsourcing.
The invention aims at the common problem of the crowdsourcing system deployed in the blockchain, specifically, as shown in the attached figure 1, the data of the crowdsourcing system is deployed in a semi-open blockchain with a Bayesian node, the maintenance of the blockchain is mainly carried out by an account book management node, the common crowdsourcing node can only read the data of the blockchain, the identities of the common node and the account book management node can be mutually converted, and in such a semi-open environment, how to meet the low delay of transactions, the expandability of the nodes and the fairness of the common activity required by the crowdsourcing system while avoiding the Bayesian error are the problems to be considered urgently. The invention designs a reputation value model to determine the influence of account management nodes in consensus activities, and mainly considers three factors for measuring the reputation value of the account management nodes:
(1) First, the account management node pays the deposit of the platform and participates in the credit value obtained by conversion of the incentive obtained by the consensus activity. Unlike traditional federation chains, the nodes responsible for maintaining blockchains are not limited to a fixed cluster, and common nodes in an open network can provide a way of paying deposit to apply for becoming ledger administration nodes, thereby participating in consensus activities. The payment of deposit participation in consensus may prevent the ledger administration node from disqualifying because the ledger administration node must counter its disqualifying costs. On the other hand, the incentive that the ledger administration node gets in consensus activities is also part of the reputation measure, which may encourage the ledger administration node to actively participate in the consensus. Meanwhile, a sigmod function is adopted to limit the credit value obtained by fund conversion, so that rights are prevented from being gathered to a enriching person.
(2) And secondly, the account book management node considers the subjective evaluation of the consumer on the service provider in crowdsourcing interaction factors, and simultaneously considers the consumption behavior evaluation of the service provider on the consumer, wherein the subjective evaluation and the consumption behavior evaluation are mutually restricted. For newly added account book management nodes, the historical evaluation of the nodes formed in crowdsourcing activities is considered, so that the nodes can obtain partial credit values, and therefore the nodes are more likely to participate in consensus activities, and the nodes are not located at the edge of the consensus cluster because of own new identities.
(3) Finally, the account book management node represents in the consensus activity, and the more successful times of the consensus activity participated by the node, the better the credit value of the node represents. The performance of the node in the consensus activity is considered, on the one hand, to encourage the node to actively participate in the consensus activity, and on the other hand, the newly added ledger administration node may be restricted because its new identity is at the favorable end (i.e. there is a greater chance to participate in the consensus activity) in the consensus cluster, because the newly added ledger administration node is a reputation value without this part.
In a specific implementation process, communication between nodes adopts an communication protocol based on IPFS, as shown in fig. 2, wherein a left graph shows that nodes N1, N2, N3 and N4 on an open network firstly need to establish contact with bootstrap nodes, and other nodes on the network can be discovered after the contact is established, so that communication is established with other nodes; the right graph shows that the nodes can directly communicate after the connection is established, and bootstrap nodes are not required to be relied on. The account management node on the consensus network contains IPFS addresses of all nodes, the connection is not required to be established through bootstrapping nodes, and the latest relevant information of the account management node is only required to be obtained through bootstrapping nodes. Meanwhile, the IPFS address of the ledger administration node is disclosed for the whole open network, and the common node can be directly connected to the corresponding ledger administration node through the IFPS address. Meanwhile, in order to better maintain the account book management node list, the function of the bootstrapping node is further improved, and the bootstrapping node is not only responsible for establishing contact of the whole open network, but also for recording each account book management node.
In the invention, in order to better distinguish the asset problems related to the consensus activities and the crowdsourcing activities, the assets are further subdivided into the liquidity assets and the fixed assets, wherein the liquidity assets are funds which can flow in the crowdsourcing transactions, and the fixed funds (deposit and incentive obtained by participating in the consensus activities) cannot circulate through the crowdsourcing transactions, and are only used for measuring the credit value of the ledger administration node. Fixed funds may be converted to mobile funds, but require payment of a certain amount of commission.
In the invention, in order to better implement a reward and punishment mechanism, a reward pool maintained by all account management nodes is designed. Funds flowing into the progressive have a commission and deposit that the ledger administration node loses trust and receives and incentives from consensus activities.
In the invention, the protocol adopts the voting mode of the PBFT, and according to the existing research, the number of nodes of the PBFT is 16-32, so that the problem that the communication overhead influences the consensus efficiency can be avoided, and when the protocol is executed, the number of account management nodes participating in the consensus is 16 each time.
As shown in figure 3, the consensus method designed by the invention mainly comprises four steps of generating a consensus list, verifying transactions, verifying blocks and stimulating and punishing. In the following, a specific explanation is made for each step (the nodes referred to below represent ledger administration nodes):
(1) Generation of consensus lists
Each account management node regularly acquires the latest account management node list from the bootstrap node, after acquiring the list, checks whether the nodes on the list are consistent with the locally maintained list, and if so, updates the locally maintained list.
In each round of consensus activities, after each account management node calculates the credit values of all account management nodes according to the credit value model, the nodes are ordered according to the sizes of the credit values, as shown in fig. 4, if the credit value of the current node is highest, the list containing the credit value is signed and then broadcast to other account management nodes. And after receiving the list, the other nodes are compared with the list obtained by local calculation, and if the list is consistent, the list confirmation information is broadcasted. If the list confirmation information received by the nodes exceeds two thirds of the number of the account management nodes, the list is considered to be valid, and each node determines a leader and a verifier of the round of consensus activities according to the list.
(2) Verification of transactions
As shown in fig. 5, the node with the highest reputation value in the verifier is responsible for selecting a group of transactions from the pool of transactions, signing the group of transactions, and broadcasting the group of transactions. After receiving the transaction group, other verifiers firstly check the validity of each transaction, execute the pre-execution operation of the transaction, generate a transaction receipt if the corresponding accounts exist and the amount related to the transaction can be successfully deducted from the account of the consumer, and indicate that the selected group of transactions are legal if the transaction number is the same as the transaction receipt number. And then checking whether the signature of the initiating node of the transaction group is correct, if so, checking whether the signatures of other verifiers are correct, and if so, broadcasting transaction confirmation messages to the other verifiers. If the verifier node receives two-thirds of the transaction confirmation messages exceeding the consensus list, it indicates that the currently selected set of transactions may be packaged into a block.
(3) Verification of blocks
As shown in fig. 6, the leader node packages the successfully verified transactions into a new block, and in the packaging process, the leader node also performs a pre-execution operation on each transaction, and packages the transaction receipt generated by the pre-execution operation into the block together with the transaction. And broadcasting the block to the verification node for secondary verification after the packing is successful. After receiving the block, the verifier verifies the hash value of the block, and if the verification is successful, a block confirmation message is sent. During the block verification timeout, the leader continually checks whether the received block acknowledgment message exceeds two-thirds of the number of nodes currently in the consensus list, and if so, considers the block to be valid and submits the block to the blockchain.
(4) Incentive and penalty
The leader submits the new block to the blockchain while executing the transaction execution operation, and updates the results of the transaction execution operation to the local database. The other ledger administration nodes then download the latest block updates from the leader node to the local. If the new block is successfully updated to the local, the current round of consensus activity is considered to be successful, and all nodes participating in the consensus activity acquire an incentive according to the contribution degree of participation, wherein the incentive is given in a prize pool maintained by the system. In the protocol execution process, any action causes the block to be submitted to fail, and the current round of consensus activity is considered to be failed, all nodes participating in the current round of consensus activity are punished, the punished mechanism is to collect partial deposit of the nodes, and the flow direction of the deposit is a prize pool maintained by the system.
Fig. 7 shows experimental simulation results, the size of the ledger administration node is set to 16, and it can be seen that when the packed transaction amount is smaller, the time consumption of generating a block by the consensus method and the zkCrowd with the double-chain structure is not great, but when the transaction amount is increased, the time consumption of generating a block by the zkCrowd is obviously increased, for example, when the transaction amount is 1500, the time consumption of generating a block by the zkCrowd is 40.0s, and the consensus method only needs 4.5s, which indicates that the consensus protocol proposed by the invention can meet the timeliness required by the crowdsourcing system.
The documents cited in the present invention are:
[1]J.Zou,B.Ye,L.Qu,Y.Wang,M.A.Orgun,and L.Li,“A Proof-of-Trust Consensus Protocol for EnhancingAccountability in Crowdsourcing Services,”IEEE Trans.Serv.Comput.,vol.12,no.3,pp.429–445,May 2019,doi:10.1109/TSC.2018.2823705.
[2]S.Zhu,H.Hu,Y.Li,and W.Li,“Hybrid Blockchain Design for Privacy Preserving Crowdsourcing Platform,”in 2019 IEEE International Conference on Blockchain(Blockchain),Atlanta,GA,USA,Jul.2019,pp.26–33.doi:10.1109/Blockchain.2019.00013.
the protection of the present invention is not limited to the above embodiments. Variations and advantages that would occur to one skilled in the art are included in the invention without departing from the spirit and scope of the inventive concept, and the scope of the invention is defined by the appended claims.
Claims (10)
1. The consensus method based on reputation value weight balance suitable for the crowdsourcing system is characterized in that the method adopts a mixed blockchain architecture to divide a blockchain network into an open network and a consensus network; the nodes in the open network engage in transaction activities, and only have reference rights to the information on the blockchain, namely common nodes, and the common nodes are divided into service providers and consumers according to the supply and demand relationship of the service; the nodes of the consensus network are responsible for updating and maintaining the blockchain, which is called an account management node, and the account management node is divided into a verifier responsible for transaction verification and block verification and a leader responsible for block packing and block updating according to a reputation value model.
2. The consensus method according to claim 1, characterized in that the consensus method comprises the steps of:
each account management node collects relevant data related to credit value calculation of all account management nodes including the account management node;
calculating the credit values of all account management nodes according to the credit value model to obtain a common node list comprising all account management nodes in the current round, wherein the node with the highest credit value is a leader node, and the rest nodes are verifier nodes;
step three, the verifier node selects a group of transactions from the transaction pool, and sends the transactions to the leader node after verification is successful;
step four, the leader packs the successfully verified transaction to generate a new block, and broadcasts the new block to the verifier node for verification;
and fifthly, updating the successfully verified block to the block chain by the leader, completing one-time consensus activity, and resetting the protocol state.
3. The consensus method as claimed in claim 2, wherein the data to be collected by the ledger administration node in step one is: deposit D paid by account management node, incentive I obtained by account management node through consensus activities, service evaluation table FBscore obtained by common node as service provider provider ＝{fb 1 ,fb 2 ,…fb m Consumer behavior evaluation table FbScore obtained by common node as consumer consumer ＝{fb 1 ,fb 2 ,…fb m And the successful times m and the failed times n of the account management node participating in the consensus activity.
4. A consensus method according to claim 3, wherein the service valuation table is generated in such a way that the service provider receives service valuations from the consumers after the service is completed, all transaction-derived service valuations forming a service valuation table; the service evaluation means that a transaction is completed, and the consumer scores the provided services of the service provider from 0 to k, namely, the service evaluation table FBScare provider Is a rating score fb of (2) m E 1 … k; after the consumer finishes the transaction and evaluates the service, the service provider can score and evaluate the consumer's consumption from 0 to k, and the consumption evaluation scores of all the transactions form a consumption evaluation table, and the consumption evaluation table FbScare consumer Is a rating score fb of (2) m E 0 … k; when the account management node participates in formula activity, the success of generating a new block is recorded as a success number, otherwise, the success number is recorded as a failure number.
5. The consensus method according to claim 2, wherein the step of generating the list of consensus nodes in the step two is:
step 2.1: each account management node calculates the credit values of all account management nodes, and a consensus node list is obtained according to the size of the credit values, after the list is obtained, if the credit value of the node i is highest, the node i is used as a leader, the node i signs the list and broadcasts the list to other account management nodes, and the other account management nodes wait for the list transmitted by the node i;
step 2.2: after receiving the list, other account management nodes compare the list with a list of consensus nodes obtained by local calculation, if the list is consistent with the list, a list confirmation message is broadcast, otherwise, the list is discarded;
step 2.3: and each account management node counts list confirmation messages uploaded by the network, if the number of the messages collected in the overtime time exceeds two thirds of the number of the account management nodes, the list is considered to be effective, and otherwise, the view switching protocol is triggered.
6. The consensus method as claimed in claim 5, wherein the step of calculating the individual ledger administration node reputation value in step 2.1 is:
step 2.1.1: according to the financial and reputation conversion formula, calculating a reputation value of each account management node obtained by the financial, wherein the calculation mode is M (t) =sigmod (sigma log (D+I)), wherein sigma is a conversion factor, D is a deposit paid by the account management node, and I is an incentive obtained by the account management node;
step 2.1.2: according to the service evaluation table and consumption behavior evaluation table formed by account management node in transaction activity, calculating positive feedback evaluation alpha and negative feedback evaluation beta of every node, service evaluation table or consumption behavior evaluation table { fb 1 ,fb 2 ,…fb m Score fb in } i ∈[1,k],i∈[1,m]If (3)
Evaluation fb of the node formed in this transaction i Is a forward evaluation, which is recorded in a set P to obtain p= { fb 1 ,fb 2 ,…fb s Calculation ∈>
Obtaining positive feedback evaluation alpha of current round of nodes (t) The method comprises the steps of carrying out a first treatment on the surface of the If->
Evaluation fb of the node formed in this transaction i Is a negative evaluation, which is recorded in a set N to give n= { fb 1 ,fb 2 ,…fb m-s Calculation of
Obtaining negative feedback evaluation beta of current round of nodes (t) The method comprises the steps of carrying out a first treatment on the surface of the Positive feedback evaluation according to two evaluation tables>
And negative feedback evaluation->
The credit value obtained by the current round of node through transaction activity is calculated by the following calculation modes: />
Wherein k is i Feedback weights representing two evaluation tables, PR being penalty factor, PR>1；
Step 2.1.3: participating in consensus activities in accordance with ledger administration nodesCalculating the credit value obtained by the node through the consensus activity by the following calculation modes
Wherein m is the success times of the consensus activities participated by the nodes, n is the verification failure times of the consensus activities of the nodes, PR is a penalty factor, PR>1；
Step 2.1.4: according to the reputation values of the three aspects generated in the steps 2.1.1-2.1.3, calculating the final reputation value of the node, wherein the calculation formula is as follows: r is R i (t)＝w 1 M i (t)+w 2 T i (t)+w 3 C i (t),
Weight w 2 ＝w 3 >w 1 。
7. The consensus method according to claim 5, wherein in the step 2.3, the step of triggering the view switching protocol is:
step 2.3.1: the account management nodes participating in the consensus activities initiate view switching messages to all account management nodes except the account management nodes;
step 2.3.2: and in the timeout period, after all account management nodes collect the view switching messages exceeding two thirds of the account management nodes, the current view number is increased by one, otherwise, the protocol state is reset, and the view number is restored to the default value.
8. The consensus method as claimed in claim 2, wherein the step of verifying the transaction by the verifier in step three is:
step 3.1: the node with the highest reputation value in the verifier is responsible for selecting a group of transactions from the transaction pool, signing and broadcasting the transactions to other verifier nodes;
step 3.2: after receiving the group of transactions, other verifier nodes check each transaction, perform transaction pre-execution operation to generate corresponding transaction receipts, if the generated receipts are consistent with the number of the transactions, continuously and sequentially checking signature correctness of the transaction group initiating nodes and other verifiers, if the signature correctness is correct, indicating that the transaction group is verified successfully, and sending transaction verification success information to other verifier nodes;
step 3.3: the number of the transaction verification success messages received by the verifier node exceeds two thirds of the current consensus node list, the group of transaction verification success is indicated, the transaction verification success messages are sent to the leader node, and if the transaction verification success messages are not received within the timeout time, the view switching protocol is triggered.
9. The consensus method according to claim 2, wherein the step of verifying the block by the verifier in step four is:
step 4.1: checking whether the signature of the block creator is correct, if not, discarding the block without broadcasting, and if so, performing the next step;
step 4.2: checking whether the signed verifier list is on a locally generated list, if not, discarding the block without broadcasting, if so, signing the block and broadcasting a block confirmation message to the network;
step 4.3: and in the timeout period, the leader checks whether enough block confirmation messages are obtained, if the number exceeds two thirds of the current consensus list, the block verification is successful, and otherwise, the view switching protocol is triggered.
10. The consensus method as claimed in claim 2, wherein in step five, when the leader submits the new block into the blockchain while executing the transaction execution operation, the result of the transaction execution operation is updated into the local database; the other account management nodes download the latest block update from the leader node to the local; if the new block is successfully updated to the local, the current round of consensus activity is considered to be successful, and all nodes participating in the consensus activity acquire an incentive according to the contribution degree of participation, wherein the incentive is given in a prize pool maintained by the system; in the protocol execution process, any action causes the block to be submitted to fail, and the current round of consensus activity is considered to be failed, all nodes participating in the current round of consensus activity are punished, the punished mechanism is to collect partial deposit of the nodes, and the flow direction of the deposit is a prize pool maintained by the system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310350174.XA CN116366669A (en) | 2023-04-04 | 2023-04-04 | Consensus method based on reputation value weight balance suitable for crowdsourcing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310350174.XA CN116366669A (en) | 2023-04-04 | 2023-04-04 | Consensus method based on reputation value weight balance suitable for crowdsourcing system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116366669A true CN116366669A (en) | 2023-06-30 |
Family
ID=86931711
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310350174.XA Pending CN116366669A (en) | 2023-04-04 | 2023-04-04 | Consensus method based on reputation value weight balance suitable for crowdsourcing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116366669A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117314473A (en) * | 2023-10-23 | 2023-12-29 | 苏州思萃区块链技术研究所有限公司 | Carbon emission data element circulation management system based on carbon verification certificate |
| CN117527834A (en) * | 2024-01-04 | 2024-02-06 | 成都理工大学 | Improved PBFT consensus method based on reputation scoring mechanism |
-
2023
- 2023-04-04 CN CN202310350174.XA patent/CN116366669A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117314473A (en) * | 2023-10-23 | 2023-12-29 | 苏州思萃区块链技术研究所有限公司 | Carbon emission data element circulation management system based on carbon verification certificate |
| CN117527834A (en) * | 2024-01-04 | 2024-02-06 | 成都理工大学 | Improved PBFT consensus method based on reputation scoring mechanism |
| CN117527834B (en) * | 2024-01-04 | 2024-03-26 | 成都理工大学 | Improved PBFT consensus method based on reputation scoring mechanism |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yuan et al. | CSEdge: Enabling collaborative edge storage for multi-access edge computing based on blockchain | |
| US11177941B2 (en) | Methods and systems for a heterogeneous multi-chain framework | |
| CN116366669A (en) | Consensus method based on reputation value weight balance suitable for crowdsourcing system | |
| US10554407B1 (en) | Protocols for decentralized networks | |
| EP4318362A1 (en) | Blockchain-based data processing method, apparatus and device, and storage medium | |
| Shibata | Proof-of-search: combining blockchain consensus formation with solving optimization problems | |
| CN111082943B (en) | Efficient block chain consensus method | |
| CN112163856A (en) | Consensus method and system for block chain and Internet of things fusion scene | |
| CN110610421A (en) | Guarantee fund management method and device under fragment framework | |
| CN112488787A (en) | Shared resource leasing method and device based on block chain and computer equipment | |
| CN114282956A (en) | Energy transaction method, device, electronic equipment and storage medium | |
| CN110851531A (en) | Cooperative edge computing method, block chain and cooperative edge computing system | |
| WO2023116790A1 (en) | Method and apparatus for executing computing task, and storage medium and electronic apparatus | |
| Khosravifar et al. | Agent-based game-theoretic model for collaborative web services: Decision making analysis | |
| CN112118138A (en) | System and method for implementing block chain consensus mechanism | |
| Li et al. | Game theory based compatible incentive mechanism design for non-cryptocurrency blockchain systems | |
| CN111582864A (en) | Block chain data volume certification consensus protocol | |
| Yue et al. | A double auction-based approach for multi-user resource allocation in mobile edge computing | |
| Hu et al. | Trusted resource allocation based on proof-of-reputation consensus mechanism for edge computing | |
| CN112565370A (en) | Method and system for verifying calculation result based on wireless communication and block chain scene | |
| Eisele et al. | Mechanisms for outsourcing computation via a decentralized market | |
| CN111522884B (en) | Threat information transaction alliance chain transaction promotion method based on benefit distribution | |
| Li et al. | Resource allocation for mobile blockchain: A hierarchical combinatorial auction approach | |
| Bouchiha et al. | GuRuChain: guarantee and reputation-based blockchain service trading platform | |
| Wang et al. | A trust-incentive-based combinatorial double auction algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |