KR20220116655A - System of speculative transaction execution for Blockchain scalability and method thereof - Google Patents

Abstract

The present invention relates to a predictive transaction processing system for blockchain scalability and a method thereof. According to the present invention, the predictive transaction processing system for blockchain scalability, which is able to predictively process an off-chain transaction, and post-processes an on-chain transaction, comprises: a user terminal transmitting a request for using a service to a client; an off-chain client configuring the request transmitted from the user terminal as a transaction, and transmitting the transaction to a predictive processor of an off-chain and a blockchain of an on-chain; and the predictive processor using a data structure and calculation, and predictively processing the transaction, and transmitting the processed results to the client, and performing the post-processing for the block data transmitted from the client. The present invention aims to provide a predictive transaction processing system for blockchain scalability and a method thereof, which are capable of innovatively improving blockchain performance scalability.

Description

System of speculative transaction execution for Blockchain scalability and method thereof

The present invention relates to an off-chain predictive transaction processing system and method for increasing blockchain scalability.

In order to use blockchain-based services in real life, blockchain transaction processing speed is important, and a major obstacle to the spread of blockchain technology is low scalability. For example, Bitcoin is known to take an average of 10 minutes for a transaction to be confirmed, while Ethereum takes an average of 22 seconds.

In order to solve the block chain performance scalability, various techniques such as consensus algorithm improvement, encryption technique improvement, and off-chain transaction processing are being developed. For example, the blockchain off-chain transaction processing method is very fast compared to on-chain transaction processing in which all blockchain nodes participate. The reason for this is that rapid consensus occurs in a small network (ie, off-chain) in which only trading parties participate.

On the other hand, in order to improve the performance of a computer program, a predictive processing technique (Speculative execution) exists. The predictive processing technique is a general method to improve performance by predicting the result in advance before any operation to be executed by the program is completed, and using the predicted result value for the next operation execution. However, the predictive processing technique requires a separate post-processing process when the predicted result is different from the actual result. A separate post-processing process includes an operation that restores an operation that has failed prediction and the effects of other operations that have a dependency relationship on the operation to a stable state before failure.

An object of the present invention to solve the above problems is to provide a predictive transaction processing system and method for blockchain scalability that supports rapid processing of blockchain transactions using off-chain predictive processing techniques. have.

The predictive transaction processing system for blockchain scalability of the present invention for achieving the above object is a predictive transaction processing system for blockchain scalability that predictively processes off-chain transactions and post-processes on-chain transactions. A user terminal comprising: a user terminal transmitting a request for service use to a client; an off-chain client that composes a request received from a user terminal into a transaction and delivers it to an off-chain predictive processor and an on-chain blockchain; and a predictive processor that predictively processes a transaction by utilizing a data structure and operation, delivers the processed result to the client, and performs post-processing on the block data transmitted from the client; may include.

The predictive processor may be linked with on-chain background block synchronization to execute an operation that periodically fetches on-chain block data and updates the local confirmed state when the client is offline.

The data structure of the predictive processor includes: a predictive state information database that reflects predictive processing results on an off-chain; a history for storing transactions and their states for each unique order; a dependency information management graph for managing dependency information between transactions; and a fixed state information database for managing on-chain transaction processing results; may include.

A predictive transaction processing method for block chain scalability of the present invention for achieving another object of the present invention comprises the steps of performing a prediction operation in which a predictive processor predictively processes an off-chain transaction; performing post-processing operations for post-processing on-chain transactions; may include.

The predicting operation performing step may include: an ordering step of assigning a unique sequence number to a transaction; an execution step of executing a transaction; analyzing and calculating inter-transaction dependency information; and updating the execution result and data structure; may include.

The predictive operation performing step may include: a client sending a user terminal transaction to a predictive processor; entering the predictive processing phase and assigning a unique sequence number to the user terminal transaction; pre-writing information composed of a plurality of parameters into a local storage; storing the user terminal transaction execution result value in a prediction state information database; transmitting a transaction execution result value to a client; calculating dependency information for a parametric user terminal transaction; and storing the parameters in the history and dependency information management graph of the data structure of the predictive processor; may include.

The performing post-processing operation may include: a checking step of comparing a prediction result of an off-chain transaction with an on-chain transaction execution result; determining if the prediction result of the off-chain transaction in the checking step and the on-chain transaction execution result are the same; canceling if the prediction result of the off-chain transaction in the checking step is different from the on-chain transaction execution result; a rollback step of returning the predicted state information database to a state consistent with the on-chain blockchain when the cancellation step is executed; and a re-execution step of re-executing the transactions in which the rollback step has been executed. may include.

The performing post-processing operation includes: receiving, by the predictive processor, an on-chain processed transaction, and searching for an off-chain processed transaction having the same unique identifier; determining whether an on-chain transaction has been committed; when the on-chain transaction is committed, reflecting the execution result of the on-chain transaction in the final state information database; Comparing whether an order and execution result of a transaction that has a transaction unique identifier identical to that of an on-chain processed transaction are identical to each other; updating the on-chain transaction result in the history data structure and terminating the program; may include.

The performing post-processing operation includes: receiving, by the predictive processor, an on-chain processed transaction, and searching for an off-chain processed transaction having the same unique identifier; determining whether an on-chain transaction has been committed; when the on-chain processed transaction is not committed, calculating the transaction in all predicted states that have a preceding and following relationship with the on-chain processed transaction on the dependency information management graph and including it in a set A; executing the step of checking whether the set A is empty in the dependency information management graph, and terminating if the set A is empty; if the set A is not empty, deleting the set A from the dependency information management graph and updating the state of each transaction in the set A to an abort state; rolling back the predicted state information database to the definitive state information database; and re-executing each transaction in set A against the predicted state information database and terminating the program. may include.

The predictive processing operation step includes: a transaction entering a ready state at the time of submission; changing to a pre-determined state by predictive execution; changing to a final canceled state by post-processing cancellation or to a final-confirmed state by post-processing confirmation according to an on-chain processing result; in the step of entering the ready state, changing to the pre-cancellation state if there is a dependency relationship with the previously canceled transaction; may include.

Comparing whether the order and execution result of the transaction that has the same transaction unique identifier as the on-chain processed transaction match each other may include: receiving, by the predictive processor, notification of the on-chain processed transaction; retrieving a node corresponding to an on-chain processed transaction in a dependency information management graph, and calculating a node set connected to an entry edge of the node; confirming whether the node set is an empty set or all node states of the node set are final; and returning "yes" when the state of each node in the node set is finally confirmed; returning "No" when the state of each node of the node set is not finally confirmed; may include.

According to the predictive transaction processing system and method for block chain scalability of the present invention, a distributed consensus with high on-chain delay is achieved by predictively processing the transaction submitted by the user terminal off-chain and transmitting the result to the user. You can see the results quickly before it's over. This has the advantage of dramatically improving transaction latency as well as blockchain performance scalability.

According to the predictive transaction processing system and method for blockchain scalability of the present invention, the predictive processor has the advantage of being applicable as a pre-processing module of various blockchain platforms.

1 is a diagram showing the configuration of a predictive transaction processing system for block chain scalability of the present invention.
FIG. 2 is a diagram illustrating a data structure used for transaction processing by a predictive processor in the system of FIG. 1 .
3 is a diagram illustrating an operation performed for transaction processing by a predictive processor in the system of FIG. 1 .
4 is a diagram illustrating a transaction state change diagram defined by a predictive processor in the system of FIG. 1 .
5 is a diagram illustrating a predictive processing step operation for a client transaction of a predictive processor in the system of FIG. 1 .
6A and 6B are diagrams illustrating post-processing step operations for an on-chain transaction of the predictive processor in the main operation of the predictive processor of FIG. 4 .
7 is a diagram illustrating the steps of comparing the order and execution results for the on-chain transaction (T′) and the off-chain transaction (T) of FIGS. 6A and 6B .

Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that all modifications, equivalents and substitutes included in the spirit and scope of the present invention are included. In describing each figure, like reference numerals have been used for like elements.

Terms such as first, second, A, B, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. The term “and/or” includes a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being “connected” or “connected” to another component, it is understood that the other component may be directly connected or connected to the other component, but other components may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that there is no other element in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that this does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the accompanying drawings.

1 is a diagram showing the configuration of a predictive transaction processing system for block chain scalability of the present invention.

Referring to FIG. 1 , the predictive transaction processing system for blockchain scalability of the present invention includes a user terminal 110 , an off-chain 100 predictive processor 101 and a client 102 , and an on-chain 120 . ) is included.

The user terminal 110 may be regarded as a blockchain-based service user, and transmits a request 111 for service use to the client 102 . The client 102 composes the received request as a transaction 104 and simultaneously transmits it to the predictive processor 101 of the off-chain 100 and the on-chain 120 block chain. While the transaction processing of the on-chain 120 is in progress, the speculative processor 101 of the off-chain 100 performs speculative execution of the transaction by utilizing the data structure and main operation.

The predictive processor 101 delivers the processed result to the client 102 , and the client 102 delivers the final result to the user terminal 110 . And when the on-chain 120 transaction result is transmitted in block form 106 and received by the client 102 , the client 102 transmits 103 it to the predictive processor 101 .

For the received block data 103, the predictive processor 101 performs a post-processing step, including a step of comparing the transaction result predicted on the off-chain 100 with the transaction result on the on-chain 120, and The steps include final confirmation of the transaction state or transaction cancellation, state rollback, and transaction re-execution depending on whether the result is the same.

In addition, background block synchronization 121 is an operation in which when the client 102 is offline, the predictive processor 101 periodically fetches the on-chain 120 block data without the help of the client 102 to update the local fixed state. to be.

FIG. 2 is a block diagram illustrating a data structure used for transaction processing by a predictive processor in the system of FIG. 1 .

Referring to FIG. 2 , the data structures used by the predictive processor 101 for predictive processing and post-processing include a prediction state information database (DB) 131 , a definite state information database (DB) 134 , and , a history 132 , and a dependency information management graph 133 .

The predictive state information database 131 reflects the predictive processing result on the off-chain 100 .

The confirmed state information database 134 manages the transaction processing results on the on-chain 120 .

The history 132 stores transactions and their states for each unique order.

The dependency information management graph 133 manages inter-transaction dependency information.

3 is a flowchart illustrating an operation performed by the predictive processor 101 for transaction processing in the system of FIG. 1 .

Referring to FIG. 3 , the steps of configuring the predictive processing operation step S141 include allocating a unique sequence number for each transaction (S110), executing the transaction (S120), analyzing and calculating inter-transaction dependency information. step (S130), and updating the execution result and data structure (S140).

The step of configuring the post-processing step (S142) is a checking step (S210) of comparing the prediction result of the transaction on the off-chain 100 and the transaction execution result on the on-chain 120 (S210), and a step of confirming if the result is correct ( S220), a step of canceling if wrong (S230), a rollback step of returning the predicted state information database (DB) to a state consistent with the on-chain blockchain in case of cancellation (S240), re-executing the rewound transactions (re -execution) includes a step (S250).

4 is a flowchart illustrating a transaction state change diagram defined by the predictive processing operation step S141 in the system of FIG. 1 .

Referring to Figure 4, the transaction enters the ready state (S501) at the time of submission.

Next, it changes to the pre-determined state (S502) by the predictive execution (S506).

According to the on-chain processing result, it changes to the final cancellation state (S503) by post-processing cancellation (S507) or the final confirmation state (S505) by post-processing confirmation (S509).

In addition, in the case of having a dependency relationship with a previously canceled transaction in the preparation step (S508), it changes to the pre-cancellation state (S504).

FIG. 5 is a flowchart illustrating the predictive processing step operation for a client transaction of the predictive processor in the system of FIG. 1 ;

Referring to FIG. 5 , the predictive processing operation step S141 of the predictive processing method according to the present embodiment includes a series of steps S201 to S207.

First, the step S201 of the client transferring the user terminal transaction T to the predictive processor 101 is executed.

Next, the predictive processing step entry and assignment of a unique sequence number S to the user terminal transaction T (S202) is executed.

Then, a step (S203) of pre-writing the information (S, T, I) composed of three parameters to the local storage is performed.

Then, the step (S204) of storing the user terminal transaction T execution result value (R) in the prediction state information database (DB) is executed.

Here, the step (S205) of delivering the result value (R) to the client, the step (S206) of calculating the dependency information (D) for the parameter user terminal transaction (T), and the data of the parameters (T, S, D) Storing the structure history and dependency information in the management graph (S207) is executed.

6A and 6B are flowcharts illustrating the operation of the post-processing step S142 for the on-chain 120 transaction of the predictive processor 101 in the main operation of the predictive processor 101 of FIG. 4 .

6A and 6B , the post-processing method of the predictive processor 101 for the on-chain 120 processing result according to the present embodiment consists of a series of steps S300 to S314.

The predictive processor 101 receives the on-chain processed transaction (T'), searches for the past off-chain processed transaction (T) having the same unique identifier (ID) (S300), and checks whether the transaction is confirmed or not (S300). A determination is made (S301). And depending on the presence or absence, the execution path is divided into two paths, the first execution path and the second execution path of S302 and S310.

As the first execution path after S301, when the on-chain processed transaction T' is confirmed, the execution result of the on-chain 120 processed transaction T' is reflected in the confirmation state information database 134 (S302) ).

Then, it is compared whether the order and execution result of the transaction T that has the same transaction unique identifier as the on-chain processed transaction T' matches each other (S303).

If the order and execution result of the transaction (T) that has been predictively executed in the past and has the same transaction unique identifier as the on-chain processed transaction (T') in step S303 are identical to each other, the on-chain processed transaction in the history 132 data structure (T') The result is updated (S304), and the program ends.

However, if the order and execution results of the transaction (T) that have been predictively executed in the past have the same transaction unique identifier as the on-chain processed transaction (T') in step S303 and do not match each other, the dependency information management graph (G) at room temperature Compute the chained transaction (T') and all the transactions in the predicted state that are in the preceding and following relationships and include them in the set A.

As the second execution path after S301, if the on-chain processed transaction (T ') is not confirmed, the dependency information management graph (G) of all predicted states that have a trailing relationship with the on-chain processed transaction (T') The transaction is calculated and included in the set A (S310).

When the set A is calculated in the first execution path and the second execution path after S301, it is checked whether the set A is empty in the dependency information management graph (G) 133 (S311).

If the set A is not empty in the dependency information management graph (G) 133, the set A is deleted from the dependency information management graph (G) 133, and the state of each transaction of the set A is aborted in H. ) state (S312), and if the set A is empty in the dependency information management graph (G) 133, the program is terminated.

Thereafter, the predicted state information database 131 is rolled back to the definite state information database 134 (S313).

Finally, each transaction of the set A is re-executed with respect to the prediction state information database 131 (S314), and the program is terminated.

7 is a diagram illustrating in more detail the step S303 of comparing the order and execution results of the on-chain processed transaction T′ and the off-chain processed transaction T of FIGS. 6A and 6B .

Referring to FIG. 7 , the predictive processor 101 is notified of the on-chain processed transaction T' (S401).

In the dependency information management graph (G), a node corresponding to the on-chain processed transaction (T') is searched for, and a node set (N) connected to the entry edge of the node is calculated (S402).

It is checked whether the node set N is an empty set or whether the state of each node of the node set N is finally confirmed (S403).

When all the states of each node of the node set N are finally confirmed, "yes" is returned (S404), and when all the states of each node of the node set N are not finally confirmed, "no" is returned (S405) ).

As a method for implementing a predictive transaction processing system for block chain scalability of the present invention, a predictive processor module is defined.

The predictive processor processes the client-submitted transaction speculatively before going through the distributed consensus on the blockchain, and quickly delivers a response to the client, thereby supporting ultra-low latency transactions. At this time, it proceeds asynchronously with the distributed consensus on the block chain, and according to the result of the distributed consensus on the block chain, the prediction processor is post-processed for the final commit or abort of the predictive processing result. -processing).

The data structure maintained by the prediction processor is a prediction state database (DB) that stores the result of a transaction executed predictively, that is, the prediction state, and the confirmation state that stores the commit state according to the blockchain distributed consensus. A state database (DB), a history log containing all predicted transaction states and their execution history up to the finalized state, and a directed acyclic graph showing the read/write set dependency relationship between predicted execution transactions. DAG) structure's dependency information, etc.

The transaction processing process of the prediction processor includes an off-chain predictive processing step that proceeds with the predictive execution of the transaction, and a post-processing step based on the on-chain consensus result.

In one embodiment, the predictive processing step includes: allocating an execution order number to the transaction received from the client (order), executing the transaction according to the smart contract logic (execute), reading/reading the execution result to the transaction It proceeds with a step of analyzing the read/write set dependency information (build), and a step of updating the related data structure (update).

In one embodiment, in the post-processing step, it proceeds based on block information agreed on on-chain, and the predictive processor performs post-processing for the transactions stored in each block. In the post-processing step, a check step that compares prediction results for each transaction within a block, a step of committing if the prediction result and on-chain confirmation result are the same according to the check result, or aborting otherwise is composed of In case of cancellation, a rollback step of invalidating the state update by the canceled transaction is performed, a notification is delivered to the client about the rewound transactions, and a re-execute step is performed.

In one embodiment, the prediction processor maintains a smart contract, manages the latest data state information, and maintains on-chain ledger data to verify the on-chain confirmation result for predictive execution of transactions. It supports functions such as block synchronization.

In one embodiment, the prediction processor software runs on the same machine as the client.

In one embodiment, the meaning of the inter-transaction comparison of the prediction processing refers to the comparison of the front/rear edge relation of the graph node corresponding to the transaction on the dependency information management graph having the directed acyclic graph structure and the comparison of the transaction execution result.

According to the present invention, by predictively processing the transaction submitted by the user terminal off-chain and transmitting the result to the user, the result can be quickly known before the on-chain distributed agreement with high delay is finished. This has the advantage of dramatically improving transaction latency as well as blockchain performance scalability.

According to the present invention, the prediction processor has the advantage of being applicable as a pre-processing module of various blockchain platforms.

The operation of the method according to the embodiments of the present invention may be implemented as a computer-readable program or code on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices in which data that can be read by a computer system is stored. In addition, the computer-readable recording medium is distributed in a network-connected computer system so that the computer-readable program or code can be stored and executed in a distributed manner.

In addition, the computer-readable recording medium may include a hardware device specially configured to store and execute program instructions, such as ROM, RAM, and flash memory. The program instructions may include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. Although some aspects of the invention have been described in the context of an apparatus, it may also represent a description according to a corresponding method, wherein a block or apparatus corresponds to a method step or feature of a method step. Similarly, aspects described in the context of a method may also represent a corresponding block or item or a corresponding device feature. Some or all of the method steps may be performed by (or using) a hardware device such as, for example, a microprocessor, a programmable computer, or an electronic circuit. In some embodiments, one or more of the most important method steps may be performed by such an apparatus.

In embodiments, a programmable logic device (eg, a field programmable gate array) may be used to perform some or all of the functions of the methods described herein. In embodiments, the field programmable gate array may work with a microprocessor to perform one of the methods described herein. In general, the methods are preferably performed by some hardware device. Although described above with reference to the preferred embodiments of the present invention, those skilled in the art can variously modify and change the present invention within the scope without departing from the spirit and scope of the present invention as set forth in the claims below. You will understand that you can.

100: off-chain
101: predictive handler
102: client
110: user terminal
120: on-chain
131: prediction state information database
132: history
133: dependency information management graph
134: confirmed state information database

Claims (11)

In a predictive transaction processing system for block chain scalability that predictively processes off-chain transactions and post-processes on-chain transactions,
a user terminal transmitting a request for service use to a client;
an off-chain client that composes a request received from a user terminal into a transaction and delivers it to an off-chain predictive processor and an on-chain blockchain; and
a predictive processor that predictively processes a transaction by utilizing data structures and operations, delivers the processed result to the client, and performs post-processing on the block data delivered from the client; containing,
A predictive transaction processing system for blockchain scalability. The method of claim 1 , wherein the predictive processor comprises:
Interlocking with on-chain background block synchronization to execute an operation that periodically fetches on-chain block data and updates the local confirmed state when the client is offline,
A predictive transaction processing system for blockchain scalability. The method according to claim 1, wherein the data structure of the predictive processor is:
a predictive state information database that reflects predictive processing results on an off-chain;
a history for storing transactions and their states for each unique order;
a dependency information management graph for managing dependency information between transactions; and
a fixed state information database that manages on-chain transaction processing results; containing,
A predictive transaction processing system for blockchain scalability. performing a prediction operation in which the predictive processor predictively processes off-chain transactions; performing post-processing operations for post-processing on-chain transactions; containing,
A predictive transaction processing method for blockchain scalability. The method according to claim 4, wherein the prediction operation performing step,
a sequence step of assigning a unique sequence number to the transaction;
an execution step of executing a transaction;
analyzing and calculating inter-transaction dependency information; and
updating the execution result and data structure; containing,
A predictive transaction processing method for blockchain scalability. The method according to claim 4, wherein the prediction operation performing step,
the client passing the user terminal transaction to the predictive processor;
entering the predictive processing phase and assigning a unique sequence number to the user terminal transaction;
pre-writing information composed of a plurality of parameters into a local storage;
storing the user terminal transaction execution result value in a prediction state information database;
transmitting a transaction execution result value to a client;
calculating dependency information for a parametric user terminal transaction; and
storing the parameters in the history and dependency information management graph of the data structure of the predictive processor; containing,
A predictive transaction processing method for blockchain scalability. The method according to claim 4, wherein the post-processing operation performing step,
a checking step of comparing a prediction result of an off-chain transaction with an on-chain transaction execution result;
determining if the prediction result of the off-chain transaction in the checking step and the on-chain transaction execution result are the same;
canceling if the prediction result of the off-chain transaction in the checking step is different from the on-chain transaction execution result;
a rollback step of returning the predicted state information database to a state consistent with the on-chain blockchain when the cancellation step is executed; and
a re-execution step of re-executing the transactions in which the rollback step has been executed; containing,
A predictive transaction processing method for blockchain scalability. The method according to claim 4, wherein the post-processing operation performing step,
receiving, by the predictive processor, an on-chain processed transaction, and searching for an off-chain processed transaction having the same unique identifier;
determining whether an on-chain transaction has been committed;
when the on-chain transaction is committed, reflecting the execution result of the on-chain transaction in the final state information database;
Comparing whether an order and execution result of a transaction that has a transaction unique identifier identical to that of an on-chain processed transaction are identical to each other;
updating the on-chain transaction result in the history data structure and terminating the program; containing,
A predictive transaction processing method for blockchain scalability. The method according to claim 4, wherein the post-processing operation performing step,
receiving, by the predictive processor, an on-chain processed transaction, and searching for an off-chain processed transaction having the same unique identifier;
determining whether an on-chain transaction has been committed;
If the on-chain processed transaction is not committed, calculating the transaction in all predicted states that have a preceding and subsequent relationship with the on-chain processed transaction on the dependency information management graph and including it in a set A;
executing the step of checking whether the set A is empty in the dependency information management graph, and terminating if the set A is empty;
if the set A is not empty, deleting the set A from the dependency information management graph and updating the state of each transaction in the set A to an abort state;
rolling back the predicted state information database to the definitive state information database; and
re-executing each transaction in set A against the predicted state information database and terminating the program; containing,
A predictive transaction processing method for blockchain scalability. The method of claim 4, wherein the predictive processing operation step comprises:
the transaction entering a ready state at the time of submission;
changing to a pre-determined state by predictive execution;
changing to a final canceled state by post-processing cancellation or to a final-confirmed state by post-processing confirmation according to an on-chain processing result;
in the step of entering the ready state, changing to the pre-cancellation state if there is a dependency relationship with the previously canceled transaction; containing,
A predictive transaction processing method for blockchain scalability. The method according to claim 8, wherein the step of comparing whether the order and execution result of the transaction that has the same transaction unique identifier as the on-chain processed transaction match each other,
receiving, by the predictive processor, a transaction completed on-chain;
retrieving a node corresponding to an on-chain processed transaction in the dependency information management graph, and calculating a node set connected to an entry edge of the node;
confirming whether the node set is an empty set or all node states of the node set are final; and
returning "yes" when the state of each node in the node set is finally confirmed;
returning "No" when the state of each node of the node set is not finally confirmed; containing,
A predictive transaction processing method for blockchain scalability.

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