WO2024066007A1 - Transaction execution method in blockchain system, consensus node, and blockchain system - Google Patents

Abstract

A transaction execution method in a blockchain system, a consensus node, and a blockchain system. The blockchain system comprises a first-type consensus node and a second-type consensus node. The first-type consensus node stores state data, which comprises a plurality of states, and the second-type consensus node stores verification data, which is used for verifying the plurality of states. The method is executed by the second-type consensus node, and comprises: acquiring from the first-type consensus node a read set of a plurality of transactions to be executed, the read set comprising a first state that is read according to the plurality of transactions; on the basis of the verification data, verifying the read set; in cases in which verification succeeds, executing the plurality of transactions according to the read set, and obtaining a write set, the write set comprising a second state for updating the state data; and according to the write set, updating the verification data.

Description

Transaction execution method in blockchain system, consensus node and blockchain system

This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on September 30, 2022, with application number 202211214892.6 and application name “Transaction Execution Method, Consensus Node and Blockchain System in Blockchain System”, the entire contents of which are incorporated by reference in this application.

Technical Field

The embodiments of this specification belong to the field of blockchain technology, and in particular, relate to a transaction execution method, a consensus node, and a blockchain system in a blockchain system.

Background technique

Blockchain is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. In the blockchain system, data blocks are combined into a chain data structure in a sequential manner according to time order, and a distributed ledger that cannot be tampered with or forged is guaranteed by cryptography. Due to the characteristics of decentralization, information cannot be tampered with, and autonomy, blockchain has also received more and more attention and application. In the blockchain system, the full node is generally used as the minimum facility to participate in the consensus. The full node needs to include the full amount of data to support the consensus function.

Summary of the invention

The purpose of the present invention is to provide a light consensus node and transaction execution solution in a blockchain system, which can greatly save storage resources in the blockchain system and improve system efficiency.

In a first aspect, the present specification provides a transaction execution method in a blockchain system, the blockchain system comprising a first type of consensus node and a second type of consensus node, the first type of consensus node storing state data, the state data comprising a plurality of states, the second type of consensus node storing verification data, the verification data corresponding to the plurality of states, the method being executed by the second type of consensus node, comprising:

Obtaining a read set of multiple transactions to be executed from a consensus node of the first type, the read set including a first state read according to the multiple transactions;

verifying the read set based on the verification data;

If the verification passes, executing the multiple transactions according to the read set to obtain a write set, wherein the write set includes a second state for updating the state data;

The verification data is updated according to the write set.

A second aspect of the present specification provides a blockchain system, including a first type of consensus node and a second type of consensus node, wherein the first type of consensus node stores state data, wherein the state data includes multiple states, and the second type of consensus node stores verification data, wherein the verification data corresponds to the multiple states.

The first type of consensus node is used to send a read set of multiple transactions to be executed to the second type of consensus node, where the read set includes a first state read according to the multiple transactions;

The second type of consensus node is used to verify the read set based on the verification data; if the verification passes, the multiple transactions are executed according to the read set to obtain a write set, and the write set includes a second state for updating the state data; and the verification data is updated according to the write set.

A third aspect of the present specification provides a consensus node in a blockchain system, the blockchain system comprising a first type of consensus node and a second type of consensus node, the first type of consensus node stores state data, the state data includes multiple states, the second type of consensus node stores verification data, the verification data corresponds to the multiple states, and the second type of consensus node includes:

an acquisition unit, configured to acquire, from a consensus node of the first type, a read set of a plurality of transactions to be executed, the read set comprising a first state read according to the plurality of transactions;

a verification unit, configured to verify the read set based on the verification data;

an execution unit, configured to execute the plurality of transactions according to the read set to obtain a write set when the verification passes, wherein the write set includes a second state for updating the state data;

An updating unit is used to update the verification data according to the write set.

A fourth aspect of the present specification provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method described in the first aspect.

A fifth aspect of this specification provides a consensus node, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, the method described in the first aspect is implemented.

In the scheme of the embodiments of the present specification, only the verification data of the state is saved in the light consensus node. The full consensus node sends the read set of the transaction to be executed to the light consensus node, so that the light consensus node can verify the read set based on the verification data, and then execute the transaction according to the read set after the verification is passed, which greatly saves the hardware cost and time cost of data storage and improves the performance and efficiency of the blockchain system.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of this specification, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

FIG1 shows a diagram of a blockchain architecture in one embodiment;

Figure 2 is a schematic diagram of the consensus process in the PBFT consensus algorithm;

FIG3 is a schematic diagram of the structure of blockchain data storage of consensus nodes in the related art;

FIG4 is a schematic diagram of the structure of an MPT tree;

FIG5 is a schematic diagram of a state hash value tree and a storage hash value tree in an LVP in an embodiment of this specification;

FIG6 is a schematic diagram of a state hash value tree in an embodiment of this specification;

FIG7 is a flow chart of a transaction execution method in an embodiment of the present specification;

FIG8 is a structural diagram of a light consensus node in a blockchain system in an embodiment of this specification.

Detailed ways

In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

FIG1 shows a diagram of a blockchain architecture in an embodiment. In the diagram of the blockchain architecture shown in FIG1 , a blockchain 100 includes N nodes, and FIG1 schematically shows nodes 1 to 8. The lines between the nodes schematically represent a P2P (Peer to Peer) connection, and the connection may be, for example, a TCP connection, etc., for transmitting data between nodes.

Transactions in the blockchain field can refer to task units executed and recorded in the blockchain. Transactions usually include a send field (From), a receive field (To), and a data field (Data). Among them, in the case of a transfer transaction, the From field indicates the account address that initiates the transaction (i.e., initiates a transfer task to another account), the To field indicates the account address that receives the transaction (i.e., receives the transfer), and the Data field includes the transfer amount.

The blockchain can provide the function of smart contracts. Smart contracts on the blockchain are contracts that can be triggered and executed by transactions on the blockchain system. Smart contracts can be defined in the form of code. Calling a smart contract in the blockchain is to initiate a transaction pointing to the smart contract address, so that each node in the blockchain can run the smart contract code in a distributed manner.

In the scenario of deploying a contract, for example, Bob sends a transaction containing information about creating a smart contract (i.e., deploying a contract) to the blockchain shown in Figure 1. The data field of the transaction includes the code of the contract to be created (such as bytecode or machine code), and the to field of the transaction is empty to indicate that the transaction is used to deploy a contract. After the nodes reach an agreement through the consensus mechanism, the contract address "0x6f8ae93..." of the contract is determined. Each node adds a contract account corresponding to the contract address of the smart contract to the state database, allocates the state storage corresponding to the contract account, and stores the contract code. The hash value of the contract code is saved in the state storage of the contract, so that the contract is successfully created.

In the scenario of calling a contract, for example, Bob sends a transaction for calling a smart contract to the blockchain shown in Figure 1. The from field of the transaction is the address of the account of the transaction initiator (i.e. Bob), the to field is the above-mentioned "0x6f8ae93...", that is, the address of the smart contract being called, and the data field of the transaction includes the method and parameters for calling the smart contract. After consensus is reached on the transaction in the blockchain, each node in the blockchain can execute the transaction separately, thereby executing the contract separately, and updating the status database based on the execution of the contract.

The consensus mechanism in the blockchain is a mechanism for blockchain nodes to reach a consensus on block information (or block data) across the entire network, which can ensure that the latest block is accurately added to the blockchain. The current mainstream consensus mechanisms include: Proof of Work (POW), Proof of Stake (POS), Delegated Proof of Stake (DPOS), Practical Byzantine Fault Tolerance (PBFT) algorithm, etc. Among them, in various consensus algorithms, usually after a preset number of consensus nodes reach an agreement on the data to be treated as consensus (i.e., consensus proposal), the consensus on the consensus proposal is determined to be successful. Specifically, in the PBFT algorithm, for N≥3f+1 consensus nodes, f malicious nodes can be tolerated, that is, when 2f+1 nodes among N consensus nodes reach an agreement, the consensus can be determined to be successful. In related technologies, in order to realize the consensus function, the full amount of ledgers is stored on the consensus node, that is, the status of all blocks and all accounts is stored. Thus, each node in the blockchain can generate the same state in the blockchain by executing the same transaction, so that each node in the blockchain stores the same state database.

FIG2 is a schematic diagram of the consensus process in the PBFT consensus algorithm. As shown in FIG2, according to the PBFT consensus algorithm, the consensus process can be divided into four stages: request, pre-prepare (PP), prepare (P) and commit (C). Assume that a blockchain includes four consensus nodes, node n1-node n4, wherein node n1 is, for example, a master node, and node n2-node n4 are, for example, slave nodes. According to the PBFT algorithm, f=1 malicious nodes can be tolerated in node n1-node n4. Specifically, in the request stage, a user of the blockchain can send a request to node n1 through his user device, and the request is, for example, in the form of a blockchain transaction. In the preparation stage, after receiving multiple transactions from one or more user devices, node n1 can package the multiple transactions into a consensus proposal, and send the consensus proposal and the signature of node n1 on the consensus proposal to other consensus nodes (i.e., node n2-node n4) for generating blocks. The consensus proposal may include information such as the transaction body of the multiple transactions and the submission order of the multiple transactions. In the preparation stage, each slave node can sign the consensus proposal and send it to each other node. Assuming that node n4 is a malicious node, node n1, node n2, and node n3 can determine that the preparation phase is completed and can enter the submission phase after receiving the signatures of 2f=2 other consensus nodes on the consensus proposal. For example, as shown in Figure 2, after node n1 receives the signatures of node n2 and node n3, it verifies that the signatures of node n2 and node n3 are correct signatures on the consensus proposal, and then determines that the preparation phase is completed. After node n2 receives the signature of node n3 and the signature of node n1 in the preparatory phase and verifies them, it determines that the preparation phase is completed. In the submission phase, each consensus node signs the consensus proposal in the submission phase and sends it to other consensus nodes. After receiving the signatures of 2f=2 other consensus nodes in the submission phase, each consensus node can determine that the submission phase is completed and the consensus is successful. For example, after receiving and verifying the signatures of the submission phase of nodes n2 and n3, node n1 determines that the submission phase is completed, so that node n1 can execute the multiple transactions according to the consensus proposal, generate and store blocks (such as block N) including the multiple transactions, update the world state according to the execution results of the multiple transactions, and return the execution results of the multiple transactions to the user device. Similarly, after determining that the submission phase is completed, nodes n2 and n3 execute the multiple transactions, update the world state according to the execution results of the multiple transactions, and generate and store block N. Through the above process, the storage consistency of nodes n1, n2, and n3 is achieved. In other words, nodes n1-n4 can still achieve consensus on the consensus proposal successfully and complete the execution of the block in the presence of a malicious node.

FIG3 is a schematic diagram of the structure of the blockchain data storage of the consensus node in the related art. In the blockchain data storage shown in FIG3, the block header of each block includes several fields, such as the previous block hash previous_Hash (Prev Hash in the figure), the random number Nonce (in some blockchain systems, this Nonce is not a random number, or in some blockchain systems, the Nonce in the block header is not enabled), the timestamp Timestamp, the block number Block Num, the state tree root hash State_Root, the transaction tree root hash Transaction_Root, the receipt tree root hash Receipt_Root, etc. Among them, the Prev Hash in the block header of the next block (such as block N+1) points to the previous block (such as block N), which is the block hash value of the previous block (i.e., the hash value of the block header). In this way, the next block on the blockchain is locked to the previous block through the block header. In particular, as mentioned above, state_root is the hash value of the root of the state trie consisting of the states of all accounts in the current block, such as the Merkle Patricia Tree (MPT Tree).

The MPT tree is a tree structure that combines the Merkle tree and the Patricia tree (a compressed prefix tree, a more space-saving Trie tree, a dictionary tree). The Merkle Tree algorithm calculates a hash value for each leaf node, and then connects two nodes to calculate the hash again until the top Merkle root. Ethereum uses an improved MPT tree, which is a 16-way tree structure.

The state tree contains key-value pairs (key and value pairs) of the storage content corresponding to each account in the Ethereum network. The "key" in the state tree can be a 160-bit identifier (the address of the Ethereum account), and the characters contained in this account address are distributed in each node in the path from the root node of the state tree to the leaf node. Referring to FIG3, the leaf nodes of the MPT state tree (such as node t4 and node t5) also include the Value of each account. Among them, when the account is a user account (also known as an external account), such as account A in FIG3, the Value of the account includes a counter (Nonce) and a balance (Balance). When the account is a contract account, such as account B in FIG3, the Value of the account includes a counter (Nonce), a balance (Balance), a contract code hash value (CodeHash) and a storage tree root hash value (Storage_root). Among them, the counter, for an external account, represents the number of transactions sent from the account address; for a contract account, it is the number of contracts created by the account.

The nodes in the state tree are connected by hashing. Specifically, a hash value can be generated based on the data in the child node of the parent node, and the generated hash value is stored in the parent node. Figure 4 is a schematic diagram of the structure of the MPT tree. Assume that the node marked "t2" in Figure 4 corresponds to the node t2 in the state tree in Figure 3, and the node marked "t4" corresponds to the leaf node t4 in the state tree in Figure 3. As shown in Figure 4, the states included in each leaf node in Figure 4 are respectively represented as state1, state2, state3, and state4, and each state is also the Value of each account. The characters in the left box of each node in Figure 4 are used to index the account, and the characters included in each node in the path between the leaf node and the root node are concatenated to form the account address corresponding to the leaf node. For example, each node between the leaf node where state1 is located and the root node includes the characters "f", "5" and "324", so that the account address corresponding to state1 can be obtained as "f5324".

In FIG4 , the child nodes of the node including “5” include leaf nodes. When calculating the hash (324, 74) included in the node, the following formula (1) can be used for calculation:

hash(324,74)＝hash(hash(324,hash(state1)),hash(74,hash(a,c)))  (1)

That is, when calculating the hash value hash(324, hash(state1) of the leaf node t4 in FIG4, "324" in the node t4 and the hash value hash(state1) of state1 are concatenated, and then the hash value of the concatenated data is calculated to obtain the hash value of the leaf node. When calculating the hash value hash(74, hash(a, c)) of the non-leaf node in FIG4 (for example, the node including "74"), the data in the node is directly concatenated, and then the hash value of the concatenated data is calculated. It can be understood that the hash value of the node in the state tree is a hash value calculated based on all the data of the node, and the hash value included in the node that is not a leaf node and a non-root node in the state tree is a hash value obtained by concatenating the hash values of all its child nodes and hashing them.

In this way, the hash value included in each node between the leaf node and the root node can be calculated from bottom to top in the state tree, so that the calculated hash value of node t2 in Figure 3 can be concatenated with the hash value of node t3, and the concatenated data is hashed to generate the hash value of node t1. The hash value of node t1 is the state root of the state tree, which is recorded in the State_Root field of block N.

In a variation of the MPT tree, a branch node may be included, and the branch node may be connected to multiple child nodes, and the branch node includes the hash value of the data in each child node connected to it, that is, the branch node includes multiple hash values corresponding to multiple main nodes, and the leaf node is connected after the branch node. This variation also includes an extension node, which can be connected before or after the branch node, and the extension node has a child node, and the extension node includes the hash value of all data in the child nodes connected to it. In this MPT tree variation, the hash value of the root node can also be recursively obtained based on the nodes of each layer. The embodiment of this specification is also applicable to this MPT tree variation.

After the smart contract is deployed on the blockchain, a corresponding contract account will be generated. This contract account generally has some states, which are defined by the state variables in the smart contract and generate new values when the smart contract is created and executed. As shown in Figure 3, the relevant states of the contract are stored in the storage trie, and Figure 3 schematically shows the storage trie of the contract corresponding to account B. The hash value of the root node st1 of the storage tree is stored in the above storage_root, so that all states of the contract are locked to the Value (i.e., account state) of the contract account in the state tree through the root hash. The storage tree can also have an MPT tree structure. Similar to the state tree shown in Figure 4, each node in the path from the root node to the leaf node can include characters for addressing the variable name, and the leaf node stores the value of the variable, so that the key-value mapping from the variable name (also called the state address) to the state value is stored in the storage tree. For example, referring to the storage tree in Figure 3, the leaf nodes st2 and st3 of the storage tree include the Value of variable a, the Value of variable b, etc. Taking variable a as an example, the characters included in each node in the node path from the root node to the leaf node st2 in the storage tree constitute the variable name of variable a, and the variable name can similarly be composed of hexadecimal characters.

Among them, the calculation of the hash value of each node in the storage tree can refer to the method for calculating the hash value of the node in the state tree. Specifically, when calculating the hash value of a leaf node in the storage tree, the hash value of the partial key included in the leaf node and the state in the leaf node are spliced, and then the hash value of the spliced data is calculated to obtain the hash value of the leaf node. When calculating the hash value of a node that is not a leaf node and a non-root node in the storage tree, the data in the node is directly spliced, and then the hash value of the spliced data is calculated to obtain the hash value of the node.

In general, the FVP node includes tree-like state data, the leaf nodes of which include the state of the account or contract variable, each node in the path from the root node to the leaf node in the state data includes the key of the state, and the parent node in the state data includes a hash value calculated based on the data in its child nodes.

Still referring to Figure 3, after executing block N, the nodes in the blockchain reach a consensus on the next batch of transactions, and execute block N+1 after the consensus is passed, thereby generating state data corresponding to block N+1 similarly to the execution of block N, and the state data includes a state tree and storage trees corresponding to each contract. Among them, the data of the state data of block N+1 that is repeated with the state data of block N can refer to the data in block N without repeated storage. In this way, when each consensus node stores complete block data and state data, a large storage space is required.

The embodiment of this specification provides a light consensus node (Light Validating Peer, LVP), in which only part of the state data is saved, for example, the hash value data in the state tree and the storage tree is saved, but the Value (i.e., each state) of each account or variable in the state tree and the storage tree is not saved. At the same time, the blockchain also includes a full consensus node (Full Validating Peer, FVP) that is the same as the consensus node in the related art. FIG5 is a schematic diagram of the state hash value tree and the storage hash value tree in the LVP in the embodiment of this specification. As shown in FIG5, in the state hash value tree and the storage hash value tree in the LVP, compared with the state tree and the storage tree in the FVP in FIG3, the state in the leaf node in the state tree and the storage tree is replaced with the hash value of the state, for example, state1 in node t4 in the state tree is replaced with hash(state1) in node t4 in the state hash value tree, and state5 in node st2 in the storage tree is replaced with hash(state5) in node st2 in the storage hash value tree. FIG6 is a schematic diagram of the state hash value tree in FIG5. As shown in Figure 6, in the state hash value tree, the leaf node includes the last character of the account address and the state hash value of the corresponding leaf node in the state tree. For example, the leaf node t4 in the state hash value tree includes the hash (state1) of "state1" in the leaf node t4 in the state tree. The hash values included in each node other than the leaf node and the root node in the state hash value tree can be generated using the same calculation method as in the state tree. For example, the hash (324, 74) in the node including "5" in Figure 6 can be calculated by the above formula (1). The storage hash value tree can also have a structure similar to the structure shown in Figure 6. In this way, the data included in the state hash value tree and the storage hash value tree other than the leaf node in Figure 5 is consistent with the corresponding nodes in the state tree and storage tree in Figure 3, so the root hash value of the node t1 in Figure 5 is consistent with the root hash value of the node t1 in Figure 3.

The state hash value tree and storage hash value tree shown in Figures 5 and 6 can be used to verify the read set received from the FVP, so these data can be collectively referred to as verification data. It can be understood that the verification data is not limited to including the structure shown in Figure 5 or Figure 6. For example, in order to verify the read set, the verification data may at least include the hash value of the state of each leaf node in the state tree and the storage tree. For the above-mentioned MPT tree variant, it is only necessary to delete the state in the leaf node in the MPT tree variant, that is, the hash value tree after the deletion can be used as the verification data in the LVP node. The following will use the state data and verification data shown in Figures 3-6 as examples to describe the consensus and transaction execution scheme in the embodiments of this specification.

In a blockchain system based on FVP and LVP, through the transaction execution solution provided in the embodiments of this specification, LVP can participate in transaction execution and update the locally stored hash value data based on the transaction execution results, which can greatly save storage resources in LVP and reduce the storage cost of the blockchain system.

FIG7 is a flow chart of a transaction execution method in an embodiment of the present specification. The method may be executed by a FVP (schematically shown as an FVP in FIG7 ) and one or more LVPs as a master node in a blockchain system, and FIG7 shows an LVP as an example. Among them, the blockchain system may include at least one FVP, and the at least one FVP may jointly determine an FVP as a master node, and nodes other than the master node in the blockchain system are slave nodes. The master node may initiate a consensus proposal to reach a consensus on the consensus proposal together with the slave nodes.

As shown in FIG. 7 , first, in step S701 , the consensus nodes in the blockchain system reach a consensus on the consensus proposal.

Assuming that FVP1 in the blockchain system is the master node, FVP1 is used as an example in the following description. FVP1 can receive transactions sent by users from user clients or other FVPs. The transaction can be a transfer transaction, or a transaction that calls a contract, etc. After receiving a certain amount of transactions, FVP1 can select multiple transactions from the received transactions for consensus to generate a new block.

FVP1 first generates a consensus proposal, which includes the arrangement order of the multiple transactions for sequencing the multiple transactions. Specifically, the consensus proposal may include a transaction list of the multiple transactions, and the transaction list includes the transaction bodies of the multiple transactions arranged in sequence. Alternatively, the consensus proposal may include a list of transaction hash values of the multiple transactions. In this embodiment, the master node can broadcast each transaction to each other consensus node through broadcasting, which can reduce the amount of data in the consensus proposal, thereby reducing the amount of data that needs to be signed during the consensus process and accelerating the consensus process. After receiving the consensus proposal, each consensus node in the blockchain can, for example, reach consensus on the consensus proposal through the consensus process shown in Figure 2, which will not be repeated here.

In step S703, the FVP sends the read-set status of multiple transactions to the LVP.

In one embodiment, after selecting multiple transactions, FVP1 may obtain read sets corresponding to the multiple transactions by pre-executing the multiple transactions. FVP1 may pre-execute the multiple transactions according to a preset arrangement order of the multiple transactions, or FVP1 may pre-execute the multiple transactions according to the order in which each transaction is received, and determine the arrangement order of the multiple transactions in the consensus proposal according to the pre-execution order of each transaction.

When FVP1 reads the value of an account or contract variable for the first time during the pre-execution of multiple transactions, it reads it from the state data and generates a read set of the multiple transactions based on the value of the account or contract variable read for the first time. At the same time, FVP1 caches the value of the account or contract variable read for the first time. When the value of these first-read account or contract variables is updated during the pre-execution of multiple transactions, the value of these account or contract variables is updated in the cache. When the value of these account or contract variables is read again during the pre-execution of multiple transactions, the value of these account or contract variables in the cache is read, wherein the value of these account or contract variables read again does not need to be written into the read set of the multiple transactions.

The read set includes the status of the account and/or contract variables read from the state data according to the read operations included in the multiple transactions. The read set is also the status of the account and/or contract variables that need to be read from the state data when the multiple transactions are executed, wherein the state data, for example, includes the state tree and storage tree shown in Figure 3.

In one embodiment, FVP1 can obtain the read sets of multiple transactions, and then merge the read sets of each transaction, that is, select the key-value pairs of the variables read from the state data when reading each variable (including account and contract variables) for the first time from the read sets of multiple transactions, so as to obtain the read sets corresponding to the multiple transactions. Assuming that one of the multiple transactions includes an update to the balance of account A (for example, reducing a preset amount), the transaction needs to first read the value of account A (that is, including Nonce and Balance) when executing, and then obtain the new value of account A according to the read value of account A. For example, according to the transaction, the Nonce value is added by 1, and the Balance value is reduced by a preset amount to obtain the updated Nonce value and Balance value of account A, which constitute the updated Value of account A. Therefore, the read set of the transaction includes the key-value pairs of account A read, and the write set of the transaction includes the key-value pairs of account A written. The read set of the multiple transactions includes the Key-Value pair of account A read from the status data, where the Key is the account address of account A, and the Value is the status of account A, which includes the Nonce value and Balance value in the leaf node corresponding to account A.

Assume that one of the multiple transactions includes an update operation on variable a in the contract corresponding to account B. Since writing to variable a will result in an update to Storage_root in account B, the transaction also includes a write operation on account B. In order to write to account B and variable a, the read set of the transaction needs to include the Key-Value pair of account B and the key-value pair of variable a. Assuming that the reading of account B and variable a by the transaction is the first reading from the state data, the read sets of multiple transactions also include the key-value pair of account B and the key-value pair of variable a read from the state data based on the transaction. Among them, the key in the Key-Value pair of account B is the account address of account B, and the Value is the state of account B, which includes the values of the Nonce, Balance, CodeHash and Storage_root fields in the leaf node corresponding to account B. The key in the Key-Value pair of variable a is the variable name of variable a, and the Value is the state value of variable a. According to the read sets of the multiple transactions, when writing to account B in the execution of the transaction, the updated Storage_root can be calculated according to the updated value of variable a and merged with the Nonce, Balance, and CodeHash of account B in the read set to obtain the updated value of account B. The updated value of variable a and the updated value of account B will be recorded in the write set of the transaction for updating the status data.

After generating the read sets of the multiple transactions as described above, FVP1 may send the read sets to each LVP. FVP1 may send the read sets together with the consensus proposal to each LVP. Thus, each LVP may perform consensus on the consensus proposal and verification of the read sets in parallel, thereby improving system efficiency.

In another embodiment, after receiving the consensus proposal, LVP may perform static analysis on multiple transactions involved in the consensus proposal, analyze the transaction body of the transaction and the contract code of the contract called in the transaction, so as to determine the account and/or variable name that each transaction needs to read when executing, that is, the key in the read set of the multiple transactions. Afterwards, LVP may request the state corresponding to the key from one or more FVPs based on the key in the obtained read set. In the case where LVP requests the state of the read set from multiple FVPs, LVP may request different states from multiple FVPs in parallel, thereby improving the efficiency of obtaining the read set. After obtaining all the states in the read set from the FVP, LVP generates the read set corresponding to the multiple transactions based on the state obtained from the FVP.

In step S705, the LVP verifies whether the read set is correct based on the verification data.

In one embodiment, the state tree in FIG. 3 and the hash value of each state in the storage tree, as well as the index data to the hash value (such as an account address or a variable name) are stored in LVP as verification data. After obtaining the read sets of multiple transactions as described above, LVP can use the hash values of each state to verify each state in the read set. For example, the read set includes the Value of account A. LVP can obtain the state hash value of account A from the verification data and use the state hash value to verify the Value of account A, that is, verify whether the Value of account A in the read set corresponds to the state hash value of account A stored locally. If so, it can be determined that the Value of account A in the read set is the correct state. In the case where the read set includes the Value of account B and the Value of variable a, LVP can obtain the state hash value of account B and the state hash value of variable a from the verification data to verify the Value of account B and the Value of variable a in the read set, respectively.

In another embodiment, the state hash value tree and storage hash value tree as shown in FIG5 are stored in LVP as verification data. After obtaining the read set from the consensus proposal, LVP can perform Simplified Payment Verification (SPV) on each state in the read set based on the state hash value tree and the storage hash value tree. For example, the read set includes the Value of account A. LVP can calculate the hash value (e.g., hash1) of the Value of account A in the read set, and calculate the hash value of each node layer by layer based on the values of other leaf nodes in the state hash value tree (i.e., the state hash value) and hash1 until the root hash value of the state hash value tree (e.g., root1) is calculated, and it is determined whether root1 is consistent with the root hash value of the state hash value tree stored in LVP. If they are consistent, the Value of account A in the read set is considered to be correct. In the case where the read set includes the Value of account B and the Value of variable a, LVP can similarly perform SPV verification on the Value of account B and the Value of variable a based on the state hash value tree and the storage hash value tree.

In one embodiment, after receiving the consensus proposal and the read sets of multiple transactions from FVP1, LVP can verify the read sets based on the verification data in parallel while reaching consensus on the consensus proposal. Alternatively, after LVP receives the consensus proposal and obtains the read sets of the multiple transactions from FVP according to the consensus proposal, since the consensus process is long, the consensus process may not be completed after LVP obtains the read sets of multiple transactions. Therefore, LVP can also verify the read sets based on the verification data in parallel while reaching consensus on the consensus proposal.

In one embodiment, when verification data corresponding to the above-mentioned MPT tree variant is stored in the LVP, since the verification data similarly includes hash values of each state in the MPT tree variant, and each layer of nodes in the verification data is connected by hash, the read set can be similarly verified based on the verification data, which will not be repeated here.

In addition, the block headers of each block can also be stored in LVP. As shown in Figure 3, the block header can include the root hash value of the state tree, the root hash value of the transaction tree, and the root hash value of the receipt tree. The block header can be used to perform SPV verification on transaction, receipt and other data, and can be used to generate the block header of the next block.

In step S707 , the LVP executes multiple transactions according to the read set.

After the consensus proposal is successfully reached and the LVP passes the verification of the read set, the LVP can execute multiple transactions in the consensus proposal based on the status in the read set. Specifically, when the LVP needs to read the status of an account or variable in the process of executing a transaction, if it is the first time to read the account or variable, the status of the account or variable can be found from the read set, and the transaction is executed based on the status of the account or variable. According to the write operation on the account or contract variable in the transaction, the write set of the transaction is obtained, and the write set includes the key-value pair of the account or the key-value pair of the contract account and the contract variable, which is used to update the status in the status data. After reading the status of the account or contract variable from the read set, the LVP can cache the status, and when executing the write to the account or contract variable, update the status of the account or contract variable in the cache, so as to be used for the subsequent reading of the status of the account or contract variable in the process of executing the transaction. Since the status of the account or variable in the read set has been verified, that is, it is the current correct status of the account or variable, the execution result obtained by executing the transaction based on the status in the read set is consistent with the execution result obtained by FVP executing the transaction based on the status in the status data.

Specifically, assuming that one of the multiple transactions described above includes an update to the balance of account A, LVP first reads the value of account A from the read set of multiple transactions (assuming the read value is V1), and updates V1 according to the transaction to obtain the updated value of account A (assuming the value is V2), where V2 includes the updated Nonce value and the updated Balance value, so that the updated key-value pair of account A can be written in the write set of the transaction.

Assuming that as described above, one of the multiple transactions includes the writing of variable a of the contract corresponding to account B, LVP first reads the value of account B (assumed to be V3) and the value of variable a (assumed to be V4) from the read set of multiple transactions, processes V4 according to the transaction, obtains the updated value of variable a (assumed to be V5), calculates the hash value of V5, substitutes it into the storage hash value tree in Figure 5, calculates the hash value of the root node st1, and uses the hash value of the root node st1 as the updated storage_root of account B. Combined with the Nonce, Balance and CodeHash of account B in the read set of the transaction, the updated value of account B (assumed to be V6) is calculated, so that the updated key-value pair of account B and the updated key-value pair of variable a can be included in the write set of the transaction.

While LVP is executing multiple transactions according to the read set, if FVP1 has previously pre-executed multiple transactions, since, as mentioned above, the order in which FVP1 pre-executes the multiple transactions corresponds to the arrangement order of the multiple transactions in the consensus proposal, the reading, updating, and writing of the state by FVP1 when pre-executing multiple transactions are consistent with those when executing multiple transactions, so that the write set obtained by pre-executing multiple transactions can be used as the write set for executing the multiple transactions, and the receipts of the multiple transactions can be obtained based on the write set. If FVP1 has not previously pre-executed multiple transactions, the multiple transactions can be executed according to the read set or by reading the state from the state data in the arrangement order of the multiple transactions in the consensus proposal. In the above two methods, the write set and receipts of the multiple transactions obtained in FVP1 are consistent with the write set and receipts of the multiple transactions executed by LVP.

Optionally, after each consensus node (including FVP and LVP) in the blockchain system completes the execution of the multiple transactions, it can reach a consensus on the execution results of the multiple transactions.

The consensus nodes can similarly reach consensus on the execution results of multiple transactions through the consensus process shown in FIG2. Specifically, after executing multiple transactions and obtaining the write sets and receipts of each transaction, each consensus node can calculate the state tree root hash values, transaction tree root hash values, and receipt tree root hash values corresponding to the multiple transactions based on the transaction bodies, write sets, and receipts of the multiple transactions. The block hash (i.e., the block header hash value of block B1) corresponding to the multiple transactions is calculated based on the state tree root hash values, transaction tree root hash values, receipt tree root hash values, and the block hash of the previous block (i.e., the block header hash value, as shown in Prev Hash in FIG3). FVP1 can send a consensus proposal to other consensus nodes in the PP phase, and the consensus proposal includes the block hash of block B1. After receiving the consensus proposal, LVP can compare whether the block hash received from FVP1 is consistent with the block hash of block B1 calculated by itself. If they are consistent, the block hash is signed and sent to other consensus nodes. After completing the PP stage, P stage, and C stage in Figure 3, the consensus on the block hash is completed. After the consensus nodes complete the consensus on the block hash, it can be ensured that the execution results of multiple transactions by each consensus node are consistent, so that each node can update the storage according to the execution results of multiple transactions.

In step S709, the LVP updates the verification data according to the write sets of the multiple transactions.

Specifically, after obtaining the write sets of each transaction, LVP obtains the write sets corresponding to the multiple transactions (e.g., wset1) according to the write sets of each transaction, and the write set wset1 includes the key-value pairs of the accounts or the key-value pairs of the contract accounts and contract variables that will be used to update the state data according to the write operations of the multiple transactions. After successfully reaching a consensus on the execution results of multiple transactions, LVP can update the verification data in LVP based on the hash values of each state in wset1.

In one embodiment, the verification data in LVP includes the hash value of the state of each account and each contract variable. Assuming that the write set wset1 includes the key-value pair of account A to be written, LVP can find the storage location of the value hash value corresponding to the key in the verification data based on the key of account A in wset1, and write the hash value of the state corresponding to the key in wset1 to the storage location.

Assuming that the write set wset1 includes the key-value pair of account B to be written and the key-value pair of variable a, LVP first calculates the updated state hash value based on the updated value of variable a, and updates the state hash value of variable a in the verification data. Afterwards, LVP calculates the updated state hash value based on the updated value of account B, and updates the state hash value of account B in the verification data.

In another embodiment, the verification data in the LVP includes a state hash value tree and a storage hash value tree as shown in FIG5 , and the LVP may first update the state hash values in the leaf nodes corresponding to the multiple states in the write set in the state hash value tree and the storage hash value tree as described in the previous embodiment. Then, based on the updated leaf nodes, the hash values included in the nodes at each level in the state hash value tree and the storage hash value tree may be updated upward until the hash values of the root nodes of the state hash value tree and the storage hash value tree are updated.

In addition, after LVP completes consensus on the block hash, it can store the block header of the generated block. As shown in Figure 3, the block header can include the root hash value of the state tree, the root hash value of the transaction tree, and the root hash value of the receipt tree. The block header can be used to perform SPV verification on data such as transactions and receipts, and can be used to generate the block header of the next block.

While LVP is updating the storage, FVP1 is also updating the storage according to the execution results of multiple transactions. Specifically, FVP1 updates the state tree and storage tree shown in FIG3 according to the write sets of multiple transactions, and stores the block B1 corresponding to the multiple transactions, which includes a block header and a block body. The block body includes, for example, transaction bodies, receipts and other data of multiple transactions. After both LVP and FVP in the blockchain system update the storage according to the execution results of multiple transactions, the verification data in LVP still corresponds to the state data in FVP, so as to continue to reach consensus on the next batch of multiple transactions.

The solution of the embodiments of this specification only stores lightweight storage in LVP. LVP obtains the read set from FVP, thereby verifying the read set based on the verification data, so that the transaction execution process can be performed according to the read set after the verification is passed, which greatly saves the hardware cost and time cost of data storage and improves the performance and efficiency of the blockchain system.

In one embodiment, LVP may include a consensus device, a storage device, and an execution device, which may be separate units in a single computing device, or may be multiple separate computing devices. The storage device stores data such as verification data and block headers in the LVP.

In this embodiment, the FVP sends the consensus proposal to the consensus device to reach a consensus on the consensus proposal. The consensus device can also obtain a read set of multiple transactions from the FVP and send the read set to the storage device. Thus, the storage device can verify whether the read set is correct based on the verification data. Wherein, while the consensus device reaches a consensus on the consensus proposal, the storage device can verify the read set in parallel. In the case of successful verification, the storage device returns the verification result of the verification to the consensus device. In the case of successful consensus, the consensus device sends a transaction list and a read set of multiple transactions to the execution device, and the transaction list includes the transaction bodies of each of the multiple transactions and the arrangement order of the multiple transactions. The execution device executes multiple transactions according to the read set to obtain the execution results of each transaction, and the execution results include, for example, the write set and receipt of each transaction. The execution device returns the execution results of the multiple transactions to the consensus device, and the consensus device generates block hash values corresponding to the multiple transactions according to the execution results of the multiple transactions. The consensus nodes (including FVP and LVP) reach a consensus on the block hash value. That is, the consensus devices of each consensus node reach a consensus on the block hash value. When the consensus on the block hash value is successful, the consensus device sends the generated block header and updated verification data to the storage device for storage. The updated verification data may include, for example, the state hash value tree shown in FIG5 and the updated node value in the storage hash value tree.

FIG8 is an architecture diagram of a light consensus node in a blockchain system in an embodiment of the present specification, wherein the blockchain system includes a first type of consensus node and a second type of consensus node, wherein the first type of consensus node stores state data, wherein the state data includes multiple states, and the second type of consensus node stores verification data, wherein the verification data corresponds to the multiple states, and the second type of consensus node includes:

An acquisition unit 81 is configured to acquire a read set of multiple transactions to be executed from a consensus node of the first type, wherein the read set includes a first state read according to the multiple transactions;

A verification unit 82, configured to verify the read set based on the verification data;

An execution unit 83 is used for executing the multiple transactions according to the read set to obtain a write set when the verification passes, wherein the write set includes a second state for updating the state data;

The updating unit 84 is configured to update the verification data according to the write set.

The embodiments of this specification also provide a computer-readable storage medium on which a computer program is stored. When the computer program is executed in a computer, the computer is caused to execute the method shown in FIG. 7 .

The embodiment of this specification also provides a consensus node, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, the method shown in FIG. 7 is implemented.

In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many of the improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with hardware entity modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing programs. The original code before compilation must also be written in a specific programming language, which is called Hardware Description Language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., and the most commonly used ones are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that realizes the logic method flow.

The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer readable medium storing a computer readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that in addition to implementing the controller in a purely computer readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the means for implementing various functions included therein may also be considered as a structure within the hardware component. Or even, the means for implementing various functions may be considered as both a software module for implementing the method and a structure within the hardware component.

The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a server system. Of course, the present application does not exclude that with the development of computer technology in the future, the computer that implements the functions of the above embodiments may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

Although one or more embodiments of the present specification provide method operation steps as described in the embodiments or flow charts, more or less operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiments is only one way of executing the order of many steps, and does not represent the only execution order. When the device or terminal product in practice is executed, it can be executed in sequence or in parallel according to the method shown in the embodiments or the drawings (for example, a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment). The term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or equipment including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such process, method, product or equipment. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or equipment including the elements. For example, if the words first, second, etc. are used to represent the name, they do not represent any specific order.

For the convenience of description, the above devices are described in various modules according to their functions. Of course, when implementing one or more of the present specification, the functions of each module can be implemented in the same or more software and/or hardware, or the module implementing the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

The present invention is described with reference to the flowchart and/or block diagram of the method, device (system), and computer program product according to the embodiment of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the process and/or box in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

In a typical configuration, a computing device includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.

Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage, graphene storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined in this article, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

It should be understood by those skilled in the art that one or more embodiments of the present specification may be provided as a method, system or computer program product. Therefore, one or more embodiments of the present specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, one or more embodiments of the present specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

One or more embodiments of the present specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. In the description of this specification, the description of the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this specification. In this specification, the schematic representation of the above terms does not necessarily target the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples without contradiction.

The above description is only an example of one or more embodiments of the present specification and is not intended to limit one or more embodiments of the present specification. For those skilled in the art, one or more embodiments of the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification shall be included in the scope of the claims.

Claims (15)

1. A transaction execution method in a blockchain system, the blockchain system comprising a first type of consensus node and a second type of consensus node, the first type of consensus node storing state data, the state data comprising a plurality of states, the second type of consensus node storing verification data, the verification data corresponding to the plurality of states, the method being executed by the second type of consensus node, comprising:

   Obtaining a read set of multiple transactions to be executed from a consensus node of the first type, the read set including a first state read according to the multiple transactions;

   verifying the read set based on the verification data;

   If the verification passes, executing the multiple transactions according to the read set to obtain a write set, wherein the write set includes a second state for updating the state data;

   The verification data is updated according to the write set.
2. The method according to claim 1, further comprising, before obtaining the read set of the plurality of transactions to be executed from the consensus node of the first type, receiving a consensus proposal from a master node to reach a consensus on the consensus proposal, wherein the consensus proposal includes an arrangement order of the plurality of transactions, and the master node is a consensus node of the first type;

   In the case where the verification is passed, executing the multiple transactions according to the read set includes:

   When the verification passes and the consensus succeeds, the multiple transactions are executed according to the read set and the order in which the multiple transactions are arranged.
3. According to the method of claim 2, obtaining a read set of multiple transactions to be executed from the first type of consensus node includes: receiving the read set from the master node, the read set is generated by the master node pre-executing the multiple transactions, and the pre-execution order of the multiple transactions corresponds to the arrangement order.
4. According to the method of claim 2, the verifying the read set based on the verification data comprises: while reaching consensus on the consensus proposal, verifying the read set based on the verification data in parallel.
5. According to the method of claim 1, obtaining a read set of multiple transactions to be executed from the first type of consensus node includes: determining a state to be read based on the multiple transactions, and requesting one or more first type of consensus nodes in the blockchain system to read the state to be read.
6. The method according to claim 1, further comprising:

   Reaching consensus on the write set with other consensus nodes in the blockchain;

   The updating of the verification data according to the write set includes: updating the verification data according to the write set when the consensus on the write set is successful.
7. According to the method of claim 6, the consensus on the write set with other consensus nodes in the blockchain system includes:

   Based on the execution results of the multiple transactions, block headers corresponding to the multiple transactions are generated, and the execution results of the multiple transactions include the write set; a hash value of the block header is calculated; and consensus on the hash value of the block header is reached with other consensus nodes in the blockchain system.
8. The method according to claim 7, further comprising: storing the block header.
9. The method according to claim 1, wherein the verification data includes a hash value of each of the plurality of states.
10. According to the method of claim 9, the verification data includes hash value data in a tree structure, multiple leaf nodes of the hash value data respectively include hash values of the multiple states, and the verification of the read set based on the verification data includes: performing SPV verification on the first state based on the hash value data.
11. According to the method of claim 4, the second type of consensus node comprises a consensus device and a storage device, the storage device stores the verification data, and while reaching consensus on the consensus proposal, the read set is verified based on the verification data in parallel, comprising:

    While the consensus device is reaching consensus on the consensus proposal obtained from the master node, the storage device is concurrently verifying the read set received from the consensus device based on the verification data.
12. A blockchain system includes a first type of consensus node and a second type of consensus node, wherein the first type of consensus node stores state data, wherein the state data includes a plurality of states, and the second type of consensus node stores verification data, wherein the verification data corresponds to the plurality of states.

    The first type of consensus node is used to send a read set of multiple transactions to be executed to the second type of consensus node, where the read set includes a first state read according to the multiple transactions;

    The second type of consensus node is used to verify the read set based on the verification data; if the verification passes, execute the multiple transactions according to the read set to obtain a write set, and the write set includes a second state for updating the state data; update the verification data according to the write set.
13. A consensus node in a blockchain system, the blockchain system comprising a first type of consensus node and a second type of consensus node, the first type of consensus node storing state data, the state data comprising a plurality of states, the second type of consensus node storing verification data, the verification data corresponding to the plurality of states, the second type of consensus node comprising:

    an acquisition unit, configured to acquire, from a consensus node of the first type, a read set of a plurality of transactions to be executed, the read set comprising a first state read according to the plurality of transactions;

    a verification unit, configured to verify the read set based on the verification data;

    an execution unit, configured to execute the plurality of transactions according to the read set to obtain a write set when the verification passes, wherein the write set includes a second state for updating the state data;

    An updating unit is used to update the verification data according to the write set.
14. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method according to any one of claims 1 to 11.
15. A consensus node comprises a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, the method described in any one of claims 1 to 11 is implemented.

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