Introduction of blockchain consensus mechanism

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introduction blockchain consensus mechanism

Consensus mechanism (Consensus Mechanism) It is an algorithm for blockchain transactions to reach distributed consensus , With the continuous promotion of blockchain Technology , Consensus mechanism is the core of blockchain , More and more people pay attention to it . Consensus mechanism plays an important role in protecting data consistency . This article selects 8 A common consensus mechanism , According to the principle of mechanism 、 The role in the running process 、 Algorithm flow and advantages and disadvantages , Proof of workload 、 Proof of interest 、 Capacity proof and other mechanisms are introduced in detail . meanwhile , This paper also makes a comparative analysis of similar mechanisms . So as to deepen people's understanding of the consensus mechanism , Accelerate the development of blockchain technology .

 

1    introduction

 

Blockchain is the underlying technology of bitcoin , Similar to a database ledger , The consensus mechanism is the core of the rules in decentralized distributed ledgers , It determines the security of the blockchain 、 Many important features such as scalability and decentralization .

Consensus mechanism refers to the process of reaching a unified agreement on the state of the network in a decentralized way . Also known as consensus algorithms , Helps verify and verify that information is added to the ledger , Make sure that only real transactions are recorded on the blockchain [12]. therefore , Consensus mechanism is responsible for safely updating the state of data in distributed networks . Rules that have been hard coded into the protocol ensure that a unique data source can always be found and agreed upon in the global computer network . These rules protect the entire network , Realize a network without trust , Without central data or intermediaries .

The consensus mechanism is to decide which participating node should be used for bookkeeping , And important means to ensure the safe completion of transactions .[8] Consensus mechanisms need to balance efficiency and security , The more complex the security measures are , The slower the corresponding processing time . And want to improve processing speed , Simplifying the complexity of security measures is a very important step .

Consensus mechanism satisfies both consistency and effectiveness . Consistency means that all honest nodes keep the same part of the blockchain prefix , The validity means that the information released by an honest node will be recorded in its own block by all other honest nodes [11]. The consensus mechanism ensures that the blockchain is fault tolerant , So it's reliable and consistent . Unlike a centralized system , Users don't have to trust anyone in the system , The protocol rules embedded in the blockchain consensus mechanism can ensure that only valid and real transactions can be recorded in the public transparent account book , The protocol rules embedded in the network ensure that the state of the public ledger is always updated as the public consensus changes .

An important advantage of decentralized blockchain is the allocation of authorization , Anyone can get involved on the same basis . The consensus mechanism can ensure that there is no discrimination in the blockchain , So as to achieve fair distribution . Due to the open source nature of the public blockchain , So that anyone can monitor and verify that the underlying source code is fair to all participants in the network [7].

Consensus mechanism can be achieved by encouraging good behavior , In some cases , Punish bad actors to achieve this . For example, in the proof of workload mechanism , By rewarding the miners with bitcoin , Reward them with guarantees and verifications for every transaction . Any computing and security maintenance requires a lot of computing power and money , The consensus mechanism enables these resources to be better used to work for the system , Not for the system .

Common consensus mechanisms are :PoW( Proof of workload )、PoS( Proof of interest )、DPoS( Certificate of appointment )、PBFT( Practical Byzantine fault tolerance algorithm )、POOL( Validation pool ) etc. .

 

2   PoW:Proof of Work( Proof of workload )

 

2008 year , In the bitcoin white paper (Bitcoinswhitepaper) On ,PoW Get attention for the first time .PoW It's relying on machines for mathematical operations ( And or operation , Calculate a random number that meets the rules ) To get the right to book this time [1], Send the data to other nodes in the whole network , After verification by other nodes , Store the data after reaching a consensus .PoW It was originally an economic term , It's a measure set for a system to achieve a goal . A simple understanding is a proof [3], To make sure you've done a certain amount of work . The whole process of monitoring is usually extremely inefficient , Through the certification of the results of the work to prove the completion of the corresponding workload , It's a very efficient way .

Illustrate with examples ,10+?=12, Who can figure out the answer first , Who will harvest .

One sentence summary : The more you do , The more you collect ( There is and only actual labor , To get results )

chart 1: PoW How it works

2.1   A term is used to explain

hash function Hash  The hash function is a one-way encryption function , Hash algorithm can get any number of data , And return a fixed length string [6], The string is completely unique for a particular input .

Nonce  A random number that can only be used once .

The miners Miners  Independent transaction processor in cryptocurrency network , The goal is to validate the transaction . It's also known as Full Node or Node.

2.2   role

Worker   There must be a certain amount of work to be done , This amount is given by the job verifier ;

Workers can't find a way to get their work done quickly ;

Workers can't themselves ” Creating jobs ”, The work has to be released by the verifier .

Verifier   Can quickly check whether the workload is up to standard .

2.3   advantage

1. Method is simple , Easy to implement .

2. There is no need to exchange additional information between nodes to reach a consensus ( Free access between nodes ).

3. It costs a lot to destroy the system .

4. All nodes of the whole network are required to participate , Completely decentralized .

2.4   shortcoming

1. At present, bitcoin has attracted most of the world's computing power , The new blockchain must find a different hash algorithm , It's hard to use the same computing power as in the past to get the same security .

2. A lot of resources are wasted .

3. Consensus takes a long time , Not suitable for commercial applications ( It's easy to split , Need to wait for more than one confirmation , It is difficult to shorten the confirmation time of blocks ).

4. There will never be finality , A checkpoint mechanism is needed to compensate for finality .

2.5   Application example

In bitcoin , Use PoW Confirm the validity of the block ( As long as CPU The amount of work consumed can satisfy the proof mechanism of the workload , Well, unless you do a lot of work again , The information in this block cannot be changed )

2.6   Problem explanation

Why do you say PoW The problem of energy consumption is serious ?

—— Because the miners (Miners) Every guess of (guess) It takes a computer to produce a certain amount of energy . at present , The hash rate of the entire bitcoin network (Hash rate) by ~17,000,000 TH/s, That's the entire network per second 17,000,000,000,000,000,000 A guess (guess). This energy demand is roughly the same as Hungarian consumption . 

3   PoS:Proof of Stake( Proof of interest )

 

2012 year ,PoS As a little coin (Peercoin) For the first time .PoS yes PoW An upgraded consensus mechanism , You don't have to consume electricity to do calculations , According to the difficulty of obtaining the bookkeeping right of each node , Its equity is inversely proportional to its ownership , Reduce the difficulty of mining in equal proportion , To speed up the search for random numbers . To keep it simple ,PoS There are no miners in (Miners), It's a verifier (Validators). It's still a way to get accounting rights based on hash operation competition , Fault tolerance and PoW identical .PoS It's based on the amount of digital money that miners currently have , A system of interest distribution based on the amount and time of money you hold , stay PoS In mode , Yours “ dig ” The income is proportional to the age of your currency , It has nothing to do with the computing power of the computer .

Illustrate with examples ,PoS It's like money in our hands . When we have more money , The more rights you get in life . One sentence summary : The more you hold , The more you get ( You get interest when you deposit money in the bank )

 

3.1   A term is used to explain

Verifier Validators  Validator , To verify the transaction , The verifier must bet a certain amount of stake,stake The size of the validator determines the possibility of the verifier verifying the next block .

 

3.2   advantage

1. To a certain extent, it shortens the time for consensus , More efficient transfer of funds .

2. There's no longer a lot of energy and computing power to mine .

 

3.3   shortcoming

1. Or mining , In essence, there is no solution to the pain point of commercial application .

2. All confirmation is just a probability expression , It's not a matter of certainty , In theory, there may be other attack effects .

3. Degree of decentralization , It is easy for the strong to be strong , Large holders of money earn interest by holding money , And then there's a monopoly problem .

3.4   Problem explanation

PoS In improving PoW After the problem of energy consumption , What other issues need to be considered ?

—— One of the most controversial issues is , If too much weight is given to a lot of wealth or old nodes , The Internet will quickly become unfair .

surface  1: PoW and PoS Comparison

4   DPoS:Delegated Proof of Stake( Certificate of appointment )

 

And PoS The main difference is that nodes elect several agents , After authorizing a vote to a proxy , Verification and bookkeeping by agent , The wallet is the status monitor . Its compliance regulation 、 performance 、 Resource consumption and fault tolerance PoS be similar . It's like a board vote , The coin holder throws a certain number of nodes , The node selects the agent , Acting on their behalf for verification and bookkeeping .

Illustrate with examples , If the holder A Supported the agent 50 Coins , Currency holder B Supported the agent 10 Coins , that A The voting weight is B Of 5 times .

One sentence summary : The node elects several agents , Verification and bookkeeping by agent

 

4.1   Part of the

1. Select a group of block producers : The election process is made up of token The holder decides , The performance of the elected producers will affect the performance of the entire network , Which in turn affects token Interests of holders .

2.  Scheduling production

 

4.2   Algorithm flow ( Take normal operation and a few bifurcations for example )

1. Normal operation : Under normal circumstances, block producers produce in sequence , The interval is 3s. No one is missing production , Here's the longest chain ( The arrow points to the previous block ).

chart  2: Normal operation

 

2. A few forks : When not more than 1/3 Of nodes are malicious or not working , And when there's a bifurcation , The following figure B, This fork every 8 A block comes out in seconds , And every node that works normally 8 Second out 2 Block [13]. The reason is according to A,B,C,A... The order of , Each node has to wait for the corresponding time to block . According to the longest chain principle , The system still works .

chart 3: A few forks

 

4.3   advantage

1. Greatly reduce the number of nodes participating in verification and accounting , It can achieve consensus verification in seconds .

2. Through the affirmative vote system , You can make sure that even if one person has 50% Effective voting rights of , You can't choose a blocker alone , Ensure algorithm security .

3. When most people have problems ,DPoS You can still work .

 

4.4   shortcoming

1. The whole consensus mechanism still depends on token , A lot of commercial applications don't need tokens .

2. Weak centralization , The degree of decentralization is not high .

4.5   Application example

EOSIO:EOSIO By commission (DPoS) system maintenance , The system was originally developed by Larimer Created , It's still being Steemit Use .Dan Larimer For the first time in BitShares Use DPOS, It immediately became one of the fastest blockchains . later BM take DPOS introduce Steem,Steem It is considered to be one of the fastest and most stable blockchain projects , Handle more than 100 Million transactions , And use only one percent of its capacity .

 

5   PBFT:Practical ByzantineFault Tolerance( Practical Byzantine fault tolerance algorithm )

 

PBFT Is a state machine replication algorithm , Generally, there are three kinds of agreements : Agreement of conformity (agreement)、 Checkpoint protocol (checkpoint) And view change protocol (view change). To ensure activity and safety (liveness and safety) The premise of providing (n-1)/3 Fault tolerance . On Distributed Computing , Different computers exchange information through , Try to reach a consensus ; But sometimes , The system coordinates the computer (Coordinator / Commander) Or member computers (Member/Lieutanent) May be due to system error and exchange wrong messages , Lead to impact on the final system consistency [9]. The Byzantine general problem is based on how many wrong computers there are to find a possible solution , Although we can't find an absolute answer , But it can only be used to verify whether a mechanism works . The possible solution to the Byzantine problem is : stay N ≥ 3F + 1 Consistency is possible to solve . among ,N Is the total number of computers ,F Total number of computers with problems . After information is exchanged between computers , Each computer lists all the information it gets , Take most of the results as the solution .

One sentence summary : Every “ The general ” Run calculations or operations based on internal state and new messages , In order to reach a personal decision , Individuals will decide to share , On the basis of all the decisions, a consensus decision is made .

 

5.1   agreement

Agreement of conformity There are at least several stages : request (request)、 Serial number assignment (pre-prepare) And response (reply). Depending on the protocol design , It may involve interaction (prepare), Serial number confirmation (commit) Equal stage .

Checkpoint protocol The algorithm sets periodic checkpoint protocol , Synchronize the servers in the system to the same state , The system will set up a check-point The timing of the , At this time, the log can be processed regularly 、 Save resources and correct server status in time .

The view is more Exchange agreement A replica node i It detects that the master node is doing evil or offline , There will be a timeout mechanism , Start view change , And number the view v Changed to: v+1, At the same time, do not accept the message except checkpoint (checkpoint)、 View change message (view-change) And new view messages (new-view) Other requests for information .

Based on fully homomorphic encryption PSI  Fully homomorphic encryption technology enables the mathematical operation of plaintext to be carried out directly on the ciphertext without first decrypting the ciphertext . Early homomorphic encryption was inefficient , And its performance has only improved in recent years . Using fully homomorphic encryption PSI agreement , By encrypting one party with a smaller set and sending it to the other party , The other party is responsible for finding the intersection of two sets based on ciphertext , Then send the result to the other party to decrypt . Using fully homomorphic encryption PSI Can achieve relatively small interaction complexity , But its computational complexity is usually very high , This leads to inefficient protocols . therefore , Reducing computational complexity without sacrificing too much interaction complexity is based on fully homomorphic encryption PSI The main challenges to the agreement .

 

5.2   Algorithm flow

1. Client initiates message : client C Send the operation request to the master node <REQUEST,o,t,c>

   o:  Request state machine operation

   t:  Client appended timestamp

   c:  Client flags

   REQUEST: Include message content m, And a summary of the message d(m) etc.

2.  Pre preparation stage : In the preparatory stage , The master node verifies the signature of the received client request message , Verification passed , Based on the current view v Assign a serial number n To the received client request , Then send pre prepared messages to all backup node groups < <PRE-PREPARE, v, n , d>, m>

  v: View number m: Request message sent by client d: The request message m A summary of the n: Pre prepared message sequence number

The purpose of preparing messages is to prove , Make sure the request is in view v Is given the serial number n, So that messages can still be traced during view changes .

3. Preparation stage : Replica node i Received... From the master node PRE-PREPARE news , The following checks are required :

•    Master node PRE-PREPARE Is the message signature correct .

•    Whether the current replica node has received one in the same v And the number is n, But the signature is different PRE-PREPARE Information .

•   d And m Is the summary consistent .

•   n Is it in the interval [h, H] Inside .

After the verification is passed , Replica node i Send preparation messages to all replica nodes <PREPARE,v, n, d, i>, And will prepare the message and prepare the message in the node i Preservation , be used for View Change Recover the uncompleted request operation in the process . When node i Received more than 2f+1 After preparing messages for nodes , You can enter the confirmation stage . It checks the view number of these messages v, Message number n And summary d.

4. Confirmation stage : The node entering the confirmation stage sends a message to other nodes including the master node <COMMIT, v, n, d, i> Confirmation message . When node i Accept to 2f+1 individual m After confirming the message and satisfying the corresponding conditions , news m Changed to: committed-local state , Node execution m Request . At the completion of m After the requested operation , Each replica node sends a reply to the client . Get into reply Stage .

5. Respond to clients : node i return <REPLY, v, t, c, i, r> To the client ,r: Request operation result . If the client receives f+1 A the same REPLY news , It indicates that the request initiated by the client has reached the consensus of the whole network , Otherwise, the client needs to determine whether to resend the request to the primary node .

chart 4: notes : copy 0 It's the master node , copy 3 It's a failed node ,C The client side. .

 

5.3   advantage

1. The system can operate without the existence of money ,PBFT Algorithm consensus that each node is composed of business participants or regulators , Security and stability are guaranteed by business stakeholders .

2. The delay of consensus is about 2~5 Second , It basically meets the requirements of commercial real-time processing .

3. Consensus is efficient , High throughput , It can meet the demand of high frequency trading volume .

4. Power consumption mode without proof of workload , More energy saving and environmental protection .

 

5.4   shortcoming

1. Limited by the number of nodes and nodes need to be elected or licensed , Scalability and decentralization are weak .

2. Low fault tolerance , When there is 1/3 Or after the bookkeeper stops working , The system will not be able to provide services ; When there is 1/3 Or a combination of the above bookkeepers , And the other two islands are divided into two separate networks , Malicious bookkeepers can cause the system to bifurcate , But it will leave behind cryptographic evidence .

 

6   POOL( Validation pool )

 

Verification pool mechanism is based on the combination of traditional distributed consistency technology and data verification mechanism , It makes in mature distributed consistent algorithms (Paxos、Raft) On the basis of , Second level consensus verification can be achieved without token .

6.1   advantage

1. It works without a token , In the mature distributed consistency algorithm (Paxos、Raft) On the basis of , Second level consensus verification .

2. Increase the speed of your application , Improve efficiency and reduce overhead .

 

6.2   shortcoming

1. Less decentralized than bitcoin .

2. More suitable for multi center business model with multi participation .

7   PoC:Proof of Capacity( Proof of capacity )

 

2015 year , The idea is Dziembowski And so on .PoC By allocating a certain amount of memory or disk space to address the challenges provided by service providers , It shows that someone has something to do with a service ( E.g. send email ) Have a legitimate interest in . although Ateniese Papers of others   The name is also “Proof-of-space”, But it's actually an adoption of MHF(Memory Hard Function, A hash algorithm whose computation cost depends on memory ) Of PoW agreement .PoC It's a way to save computing time by caching a lot of data .

Illustrate with examples , Fill the hard drive with lottery tickets , Generate a random number , Then check the person who matches the most numbers . If you have the best match , You'll win the prize .

One sentence summary : The more storage space , The more you collect ( There is and only actual labor , To get results )

 

7.1   A term is used to explain

Hash value Shabal Shabal The algorithm is a very slow algorithm , Allows the input of any length of ordinal sequence , Even an empty sequence . Also suitable for byte streams of any length , But because of security , The suitable length should be less than 27 position . The input length can be the sum of any integer value 8 Multiple . If given a bit Sequence , Index it in left and right order , The index of the first place is 0. Use left and right to describe an ordered sequence of bits : The first bit in the sequence is called the leftmost bit , The last one is called rightmost .

Plotting mapping Generate a file that stores a large number of precomputed hashes , After the memory is full of hashed files , You can still participate in the block creation process . This process is called drawing .

 

7.2   Algorithm flow

1. Hard drive drawing : Depending on the size of the hard drive , It can take days or weeks to create a unique drawing file . When drawing is called Shabal Very slow hash value of . And SHA-256 Hash values are different ,Shabal It's a hash value that bitcoin miners use quickly . because Shabal Hash values are hard to calculate , So we have to pre calculate them and store them on the hard disk . This process is called drawing hard drives .

2. The actual mining of blocks : Calculation 0 To 4085 The number of buckets between . Suppose your calculation is 42. And then you're going to scoop 42 spoon nonce 1 And then use the scoop data to calculate a period of time , This is called the deadline [5]. For everything on the hard disk nonces Repeat the process . After calculating all the deadlines , You'll choose the minimum deadline . The deadline means “ Before you are allowed to forge a block , The number of seconds that must pass since the last block was forged ”. If no one else has forged a block during this time , You can forge a block and get a block reward .

chart 5: PoC The working process diagram of

7.3   advantage

1. You can use any ordinary hard drive , So other miners won't get an advantage from buying specialized equipment , For example, use ASIC Mining bitcoin .

2. Energy efficiency with hard drives is based on ASIC Of mining 30 times .

3. Capacity proves to be more decentralized , Because everyone has a hard drive . You can even get it from your Android Mining on the hard disk of the mobile phone .

4. Miners don't need to constantly upgrade their equipment . Old hard disks can store data like new ones .

5. The hard drive can be removed after mining , And use it for the original purpose .

 

7.4   shortcoming

1.   Universal evidence of capacity extraction could lead to another arms race . Today people use tb The hard disk of , But in the end we'll see pb、exabytes  and zettabytes.

2. Capacity proof is a relatively new technology , There is no rigorous testing and challenge in the real world .

3. at present , The data drawn by the hard drive is useless except for mining purposes . However , There are plans to use hard disks as redundant storage for important open source information . The hard disk can store maps 、 Wikipedia articles or other information worth preserving .

4. There are already malware mining bitcoin on people's computers . If capacity proof becomes popular , You might see malware plotting people's hard drives .

 

7.5   Problem explanation  

Why do you say PoC It's a consensus mechanism for low power consumption ?

—— In the context of capacity proof , Because the mechanical hard disk is natural to ( Relative ) Electricity is not sensitive , The cost of electricity is no longer a knock on the door for miners to join the network in the short term   Brick , And the wide adaptability of mechanical hard disk , It further reduces the difficulty for miners to join the network , At present, home computers are commonly used 1~2T Hard disk can be used as mining equipment . Further more , Capacity proof doesn't actually store network data , Even if the hard disk is damaged, it will not lead to the loss of network content , Avoided FIlecoin The impact of data loss on network usability in spatiotemporal proof .

chart  6: PoC and PoW Comparison

 

8   Paxos

 

Paxos from Lamport On 1888 In 《The Part-Time Parliament》 The paper is published for the first time .Paxos The problem solved by the algorithm is the problem of distributed consistency , That is, how each process in a distributed system can achieve a certain value ( The resolution ) To reach an agreement .

Paxos The algorithm runs in an asynchronous system that allows downtime , Reliable messaging is not required , Message loss can be tolerated 、 Delay 、 Disorder and repetition . It uses most of (Majority) The mechanism guarantees 2F+1 The ability of fault tolerance , namely 2F+1 A system of nodes allows at most F Node failures at the same time [2]. One or more proposed processes (Proposer) You can launch a proposal (Proposal),Paxos The algorithm makes one of all proposals , Agree on all the processes . The majority in the system also endorsed the proposal , That is, an agreement has been reached . At most, only one definite proposal can be agreed upon .

 

8.1   role

Proposer   Make a proposal (Proposal).Proposal Information includes proposal number (Proposal ID) And the proposed value (Value).

Acceptor  Participate in decision making , Respond Proposers Proposal for . received Proposal After that, we can accept the proposal , if Proposal Get the majority Acceptors Acceptance of , It is called the Proposal Approved .

Learner   Not involved in decision making , from Proposers/Acceptors Learn about the latest agreed proposals (Value).

 

8.2   principle

8.2.1   Safety principles

  Promise not to do wrong . 

1. Voting on an instance can only have one value approved , There can be no case where an approved value is overridden by another value ;( Let's say that there is a value that is majority Acceptors approved , Then this value can only be learned ).

2. Each node can only learn the approved value , Can't learn values that are not approved .

 

8.2.2   The principle of survival

  As long as most servers survive and communicate with each other , The following things should be done in the end :

1. Finally, a proposed value will be approved .

2. A value has been approved , Other servers will eventually learn this value .

 

8.3   Algorithm flow

 1. The first stage :Prepare Stage .Proposer towards Acceptors issue Prepare request ,Acceptors For the received Prepare Request for Promise promise .

2. The second stage :Accept Stage .Proposer Receive the majority Acceptors Committed Promise after , towards Acceptors issue Propose request , Acceptors For the received Propose Request for Accept Handle .

3. Learn Stage .Proposer After receiving the majority of Acceptors Of Accept after , It marks this time Accept success , The resolution came into being , Send the resulting decision to all Learners.

 

8.3.1   Algorithm description

 1. Prepare: Proposer Generate globally unique and incremental Proposal ID ( You can use the timestamp to add Server ID), To all Acceptors send out Prepare request , There's no need to carry the content of the proposal here , Carry only Proposal ID that will do . 

2. Propose: Proposer Receive the majority Acceptors Of Promise After response , Choose from the response Proposal ID The biggest proposal Value, As a proposal initiated this time . If all the proposals answered Value They are all null values , You can decide your own proposal Value. And then carry the current Proposal ID, To all Acceptors send out Propose request .

3. Acceptors received Prepare After the request , To make a “ Two promises , A response ”.

4. Accept: Acceptor received Propose After the request , Without breaking the promise you made before , Accept and persist the current Proposal ID And proposals Value.

5. Learn: Proposer Receive the majority Acceptors Of Accept after , The resolution came into being , Send the resulting decision to all Learners. 

chart  7: Paxos The algorithm process

 

8.3.2   Two promises , A response [4]

 1. Two promises : No longer accept Proposal ID Less than or equal to the currently requested Prepare request ; No longer accept Proposal ID Less than the currently requested Propose request .

2. A response : Don't violate previous promises , The reply has been Accept In the past proposal Proposal ID The biggest proposal Value and Proposal ID, If not, null value will be returned .

 

8.4   advantage

1. Efficient , Node communication does not need to verify the identity signature .

2. Paxos The algorithm has strict mathematical proof , The system is well designed .

3. Fault tolerance : Less than half of Acceptor invalid 、 Any number of Proposer invalid , Can run . once value The value is determined , Even if less than half of Acceptor invalid , This value can also be obtained , It's not going to change .

 

8.5   shortcoming

1. Engineering practice is difficult , Achieving industrial performance requires engineering optimization to varying degrees , And sometimes the deviation of engineering design will cause the collapse of the whole system .

2. Only applicable to permissionedsystems( The chain of private ), Only fault nodes can be accommodated (fault), No evil nodes (corrupt).

3. a CFT(Crash FaultTolerant), Byzantine fault tolerance is not supported (ByzantineFault Tolerance).

 

8.6   Problem explanation

Multi-Paxos and Paxos The relationship between ? 

—— simple Paxos The algorithm runs through multiple rounds of Prepare/Accept Process to determine a value , We call the whole process a Instance.Multi-Paxos It's through Paxos Algorithm to determine many values , And the order of these values is exactly the same at each node , To sum up, it is to determine a global order  [10].

 

9   Raft

 

Raft It started as a consensus algorithm for managing replication logs , It's a protocol for real world applications , It mainly focuses on the implementation and comprehensibility of the agreement .Raft It's a strong consensus agreement reached under a non Byzantine breakdown , Is a consistency algorithm for managing replication logs . It's primarily designed to be easy to understand , Therefore, it has chosen a very simple and clear solution in the conflict handling and other ways .Paxos The effective basic guarantee is : Any two legal sets , There must be a public member . In addition to improving the performance of the whole system, distributed system also has an important feature of improving the reliability of the system . Providing reliability can be understood as the failure of one or more machines in the system will not make the system unavailable ( Or lose data ). The key to ensure the reliability of the system is multiple copies ( That is, data needs to be backed up ), Once there are multiple copies , Faced with the problem of consistency between multiple copies for so long . Consistency algorithm is used to solve the problem of data consistency among multiple copies in distributed environment . 

The most famous consistency algorithm in the industry is famous Paxos(Chubby My author once said : There is only one consistency algorithm in the world , Namely Paxos).

but Paxos It's notoriously hard to understand , and Raft It is to explore a more understandable consistency algorithm .

 

9.1   role

Raft The system is required to have at most one at any time Leader, During normal work, only Leader and Followers.

Leader The leader Accept client requests , And to Follower Synchronization request log , When the log is synchronized to most nodes, tell Follower Submission log . All changes to the system go through Leader, A log will be written for each change (Log Entry).Leader The process after receiving the modification request is as follows , This process is called log replication (Log Replication):

  chart 8: Log copy

 

Follower Follower All nodes are represented by Follower The state of being . If not received Leader The news will become Candidate state . Accept and persist Leader Synchronized logs , stay Leader After the notification log can be submitted , Submission log .

 

Candidate The candidate Leader A temporary role in the election process . It will send to other nodes “ Canvassing for votes ”, If you get the majority of the tickets, it becomes Leader.

chart 9: The relationship between the three characters

9.2   Algorithm flow

1. Leader Election Leader election : When Follower Not received within the election timeout Leader The heartbeats of , Convert to Candidate state . To avoid electoral strife , This timeout is a 150~300ms Random number between . generally speaking , stay Raft In the system :

•    Any server can be a candidate Candidate, It sends it to other servers Follower Make a request to elect yourself .

•    The other servers agreed , issue OK. Be careful , If in the process , There is one Follower Downtime , There was no request for an election , At this point, candidates can choose themselves , As long as we reach N/2+1 Most of the tickets for , Candidates can still be Leader Of .

•    So the candidate becomes Leader leaders , It can tell voters that Follower Issue commands , Such as bookkeeping .

•    Notification of bookkeeping by heartbeat .

•    Once this Leader collapsed , that Follower One of the candidates , And send out an invitation to vote .

•   Follower After consent , It becomes Leader, Continue to undertake accounting and other guidance work .

2. Log Replication Log copy :Raft The bookkeeping process is completed in the following steps :

chart 10: Accounting process

 

For each new transaction , Repeat the process . In the process , In case of network communication failure , bring Leader Can't access most of Follower 了 , that Leader Only those that it can access can be updated normally Follower The server . And most servers Follower Because there is no Leader, They will re elect a candidate as Leader, And then this Leader Dealing with the outside world as a representative , If they are asked to add new transactions , This new Leader Just follow the above steps to inform the majority of Follower. When network communication is restored , The original Leader It becomes Follower, In the lost phase , This old man Leader Any update to is not a confirmation , Must roll back all , Receive new Leader New update of .

 

9.3   advantage

1. Than Paxos Algorithms are easier to understand , And it's easier to engineer .

2. Raft And Paxos As efficient as , Efficiency Raft Equivalent to (multi-)Paxos.

3.   Apply to permissionedsystems( The chain of private ), Only fault nodes can be accommodated (CFT), Evil nodes are not supported . The biggest fault tolerant node is (N-1)/2, among N Is the total number of nodes in the cluster . Enhanced Leader The status of , The whole agreement can be divided into two parts :Leader In time , from Leader towards Follower Synchronous log ;Leader It doesn't work , Choose a new one Leader.

4. Emphasis on legality Leader The uniqueness agreement of , They come directly from Leader Of Degree describes the process of the protocol , Also from the Leader From the point of view of proof of correctness .

 

9.4   shortcoming

1. Only applicable to permissioned systems ( The chain of private ), Only fault nodes can be accommodated (CFT), No evil nodes .

surface  2: Raft and Multi-Paxos Comparison

 

reference

 

[1]  Beccuti, J., and Jaag, C. The bitcoin mining game:On the optimality of honesty in proof-of-work consensus mechanism. WorkingPapers (2017).

[2]  From Wikipedia, t. f. e. Paxos (computer science). https://en.wikipedia.org/wiki/Paxos_(computer_science).

[3]  From Wikipedia, t. f. e. Proof of work. https://en.wikipedia.org/wiki/Proof_of_work.

[4]  Lamport, L.  Paxos madesimple.  https://www.microsoft.com/en-us/research/publication/paxos-

made-simple/?from=http%3A%2F%2Fresearch.microsoft.com%2Fen-us%2Fum%2Fpeople%2Flamport%2Fpubs%2Fpaxos-simple.pdf.

[5]  Team, E. Proof of capacity explained: Theeco-friendly mining algorithm. https://www.coinbureau.com/education/proof-of-capacity-explained/.

[6]  Du Jiangtian . Discussion on Hash Algorithm in workload proof mechanism of blockchain . Computer programming skills and maintenance  No.394, 4 (2018), 42–44.

[7]  Yang Yuguang , and Zhang Shuxin . Review and research for consensus mechanism of block chain Information security research 004, 4 (2018), 369–379.

[8]  Liang Bin . from ” Bitcoin mining ” Look at the consensus mechanism of blockchain technology . China financial computer , 9 (2016), 45–46.

[9]  Gan Jun , Li Qiang , Chen Zihao , and juck . The improvement of Byzantine fault tolerant consensus algorithm in blockchain . Computer application , 7 (2019).

[10]  Zhu Chaofan , Guo Jinwei , and Cai Peng . be based on paxos The implementation and optimization of distributed consistency algorithm . Journal of East China Normal University  ( Natural science edition ), 10 (2019), 168–177.

[11]  Cheng Shuzhi , Shi Wenxuan , and Liu Li Ting . Overview of blockchain technology .

[12]  Han Xuan , and Liu Yamin . Research on consensus mechanism in blockchain technology . Information network security , 9 (2017).

[13]  Huang Jiacheng , Xu Xinhua , and Wang Shichun . The improvement scheme of the consensus mechanism of entrusting rights and interests proof . Computer application , 7 (2019),2162–2167

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