CN113923146A - Visual block chain consensus algorithm performance test method - Google Patents
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Abstract
A visual block chain consensus algorithm performance test method is characterized in that a consensus algorithm test and visual interface, a test management interface and a test comparison interface are established at the front end, and a consensus algorithm module, a network simulation module and a data acquisition module are realized at the rear end; setting consensus algorithm parameters, network parameters, client parameters and consensus node parameters on a test and visual interface, and starting a performance test of the consensus algorithm; the back end configures a consensus algorithm module and a network simulation module according to corresponding parameters, and acquires operation related data through a data acquisition module; dynamically rendering consensus and Debug processes on a test and visual interface, and analyzing throughput, time delay and fault tolerance; and managing the test data on the test management interface, and comparing the test data on the test comparison interface. The method has the advantages of simplicity, intuition and visualization, reduces the learning difficulty, improves the learning efficiency and improves the user experience; and a front-end and back-end separation development mode is adopted, so that new functions can be added conveniently, and the method has good expansibility.
Description
Technical Field
The invention relates to the field of block chains, in particular to a visual block chain consensus algorithm performance test method.
Background
The consensus algorithm is a core element of the blockchain technology and solves the problem of mutual trust between distributed network nodes. Meanwhile, consensus algorithms are also a hot spot of distributed system research in recent years.
Currently, the study of consensus algorithms is limited by a number of factors. For researchers of the consensus algorithm, the problems of communication between nodes, node deployment, cryptography and the like need to be processed while the consensus algorithm is designed and implemented. The common recognition algorithm is tested by a large number of nodes, performance test is required to be carried out on the common recognition algorithm, meanwhile, the reliability, delay and other attributes of a network are difficult to set, the downtime and Byzantine behaviors of the nodes are difficult to set, and the performance of the common recognition algorithm is analyzed by lacking of communication data among the nodes. For learners of consensus algorithms, specific implementations of different consensus algorithms need to be known, but different consensus algorithms are often implemented by adopting different programming languages, which greatly improves learning difficulty of the consensus algorithms. Therefore, in order to improve the research efficiency of the consensus algorithm researchers and reduce the learning difficulty of the consensus algorithm learners, a performance testing method and system of the block chain consensus algorithm are introduced.
The existing block chain consensus algorithm performance test schemes are not many, real nodes are adopted for testing, intermediate nodes are adopted for testing, Docker is adopted for testing, command lines are used for visualization, computer resources occupied in the running process of the consensus algorithm are used for performance analysis, and the like. These solutions present several problems: firstly, the test mode is complex, the test system is complex to deploy, and the parameters of the test system are difficult to configure; secondly, the performance analysis of the consensus algorithm is not strict enough, and data analysis under the conditions of unreliable network, network delay, failure of the consensus nodes, Byzantine behaviors of the consensus nodes and the like is lacked; thirdly, most of the test systems only perform performance tests on the consensus algorithm of Ethern and HyperLedger Fabric, namely, only perform performance tests on the PoW and PBFT consensus algorithms, but cannot test the consensus algorithm realized by researchers, and the universality is insufficient; finally, visualization of the consensus process is not simple and intuitive enough.
Disclosure of Invention
Aiming at the problems, the invention aims to provide a visual block chain consensus algorithm performance test method, aiming at solving the problems that the block chain consensus algorithm test mode is complex, the test system deployment is complex, the test system parameters are difficult to configure, the consensus algorithm performance analysis is not rigorous enough, the test object is single, the universality is insufficient, the consensus process is not visual, and the like.
A visual block chain consensus algorithm performance test method comprises the following steps:
s1, establishing a consensus algorithm test and visualization interface, a test management interface and a test comparison interface at the front end, and establishing a consensus algorithm module, a network simulation module and a data acquisition module at the rear end;
s2, setting consensus algorithm parameters, network parameters, client parameters and consensus node parameters on a test and visualization interface, and starting a performance test of the consensus algorithm;
s3, configuring the consensus algorithm module and the network simulation module by the back end according to corresponding parameters, and collecting related data during the running of the consensus algorithm through the data collection module;
s4, dynamically rendering a consensus process and a Debug process on a test and visualization interface, and analyzing the throughput, the delay and the fault tolerance of the consensus algorithm;
and S5, managing the test data on the test management interface and comparing the test data on the test comparison interface.
Further, the consensus algorithm parameters set by the test and visualization interface include the number of consensus nodes, the id of the master node, and the number of rounds of running of the consensus algorithm, the network parameters include the reliability of the network, whether the network delays to respond, the client parameters include the id of the client and an instruction sent by the client, and the consensus node parameters include the id of a node that the user wants to disconnect and the id of a node that the user becomes a byzantine node.
Further, the test and visualization interface indicates different states of different nodes in the consensus process through different display modes, the client node, the main node and the common consensus node are respectively marked through different colors, and the timer of each node, the node being in the down state, the node being a byzantine node, the node being successfully identified or the node failing to be identified are respectively indicated through different identifiers.
Further, the test and visualization interface analyzes the throughput, the delay and the fault tolerance of the consensus algorithm through data collected by the data collection module, and visualizes the throughput, the delay and the fault tolerance through ECharts, wherein the histogram represents the number of RPCs called between the nodes and the byte size of messages transmitted between the nodes, and the broken line represents the throughput, the delay and the fault tolerance.
Further, the consensus algorithm module is used for calling different consensus algorithms, initializing the consensus nodes according to the set consensus algorithm parameters, and operating the consensus algorithm according to the set consensus algorithm operation turns.
Furthermore, the network simulation module simulates RPC remote procedure calls through a Go language reflection technology, simulates a block chain network and block chain nodes, sets network properties such as network reliability, delay and delayed response through the simulated network, and sets whether the block chain nodes are reliable or not, whether downtime or byzantine behaviors occur or not through the simulated block chain link points.
Furthermore, the data acquisition module acquires the number of RPC called between the consensus nodes, the byte size of a transmission message, the time of each round of consensus and the result of each round of consensus through related variables in the network and the consensus node structure, and provides reference data for performance analysis of the consensus algorithm.
Furthermore, the test management interface is used for managing historical test data, displaying relevant data of each round of consensus algorithm operation on the page in a table form, and editing and deleting the data.
Furthermore, the test comparison interface is used for comparing historical test data, selecting the historical test data to be compared through a multi-selection frame, selecting the number of rounds to be compared through a counter, and selecting the performance indexes to be compared through a pull-down menu.
The invention has the beneficial effects that:
the visual block chain consensus algorithm performance test method provided by the invention provides an easily-deployed, general, simple and visual test scheme for block chain consensus algorithm performance test, establishes a consensus algorithm test and visual interface, a test management interface and a test comparison interface at the front end, and realizes a consensus algorithm module, a network simulation module and a data acquisition module at the rear end. For a consensus algorithm researcher, parameters related to a consensus algorithm, a network, a client and a consensus node can be allocated at the front end, the consensus algorithm of the researcher is improved through visual Debug, the throughput, delay and fault tolerance of the consensus algorithm are analyzed through ECharts, and the consensus algorithm researcher only needs to pay attention to the realization and improvement of the consensus algorithm and does not need to pay attention to the deployment and testing processes of the nodes. For the learner of the consensus algorithm, the technical scheme provided by the invention has the advantages of simplicity, intuition and visualization, reduces the difficulty of learning the consensus algorithm, improves the learning efficiency and improves the user experience. In addition, the invention adopts a development mode of separating the front end from the back end, can conveniently add new functions and has good expansibility.
Drawings
Fig. 1 is an architecture diagram of a performance testing method for a visualized block chain consensus algorithm according to an embodiment of the present invention.
FIG. 2 is an architecture diagram of an RPC call provided in an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of an implementation manner of the consensus algorithm testing and visualization interface provided in the embodiment of the present invention.
Fig. 4 is a schematic diagram of a consensus node state provided in an embodiment of the present invention.
Fig. 5 is a schematic structural diagram of an implementation manner of the consensus algorithm test management interface provided in the embodiment of the present invention.
Fig. 6 is a schematic structural diagram of an implementation manner of a test comparison interface of a consensus algorithm provided in the embodiment of the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the drawings in the specification.
Fig. 1 is an architecture diagram of a performance testing method of a visualized block chain consensus algorithm according to this embodiment.
Specifically, the structure of the visual block chain consensus algorithm performance testing method provided by this embodiment includes: user layer, consensus layer, visualization layer, network layer, and data layer.
Preferably, the user layer 101 is configured to set a consensus algorithm and network-related parameters, perform performance analysis on the consensus algorithm, and manage and compare test data. The user layer comprises a consensus algorithm setting module, a network setting module, a client setting module, a consensus node setting module, a consensus algorithm performance analysis module, a test management module and a test comparison module. The consensus algorithm setting module can set the number of consensus nodes, client id and host node id; the network setting module can set whether the network is reliable or not, whether the network delays or not and whether the network delays response or not; the client setting module can input the sent instruction content, the running turn of the consensus algorithm and display the running result of the consensus algorithm; the common node setting module can select the nodes to be disconnected, simulate the downtime and the Byzantine behaviors of the nodes and check whether a certain node is available. And the consensus algorithm performance analysis module analyzes the throughput, the delay and the fault tolerance of the consensus algorithm through an ECharts, and displays the number of RPCs called between nodes and the byte size of a sent message in the consensus process through a bar chart. The test management module mainly edits and deletes historical test data. The test comparison module can compare historical tests and compare the throughput, delay and fault tolerance of different tests.
Preferably, the consensus layer 102 is configured to invoke different consensus algorithms, and a researcher of the consensus algorithms may test their own consensus algorithms by implementing the Make and Start methods, initialize the consensus nodes by the Make method, and run the consensus algorithms by the Start method.
Preferably, the visualization layer 103 is used for visualizing the consensus process and the Debug process, the front end acquires data related to the consensus algorithm sent by the back end, and dynamically renders the consensus process and the Debug process through the VUE.
Preferably, the network layer 104 is used for emulating a blockchain network, RPC remote procedure calls, clients, and blockchain nodes. The network layer comprises a network management module, an RPC management module, a client management module and a consensus node management module. The network management module can set whether the network is reliable or not, whether the network is delayed or not and whether the network delays response or not, the network management module maps the name and the client structure body of the client and the name and the consensus node structure body of the consensus node through the map, meanwhile, maps the condition whether the consensus node and the consensus node are available or not, the connection condition of the client and the consensus node and the connection condition of the consensus node and the consensus node through the map, receives a request sent by the client through the channel, performs corresponding processing, and receives an instruction for closing the network through the channel. The RPC management module simulates RPC remote procedure Call through a reflex mechanism of the Go language to realize a Call method and a dispatch method, the client and the consensus node Call the process of the target node through the Call method, and the target node processes the corresponding Call request through the dispatch method. The client management module mainly initializes the client and connects the client to the blockchain network. The consensus node management module can add a consensus node, delete the consensus node, determine whether the consensus node is available, and add a service of the consensus node.
Preferably, the data layer 105 is configured to obtain the number of RPCs called between nodes during operation of the consensus algorithm, the size of bytes of a transmission message, time of each round of consensus operation, and a result of each round of consensus operation, and send these data to the front end for visualization processing and performance analysis of the consensus algorithm.
The performance testing method for the visual block chain consensus algorithm provided by the embodiment mainly comprises the following steps of S1 to S5:
step S1: the consensus algorithm testing and visualization interface, the testing management interface and the testing comparison interface are established at the front end, and the consensus algorithm module, the network simulation module and the data acquisition module are realized at the rear end.
In the step, a VUE framework is adopted for development at the front end, an Element UI is adopted for fast construction of a consensus algorithm test and visualization interface, a test management interface and a test comparison interface, and EChats are adopted for visualization of data; the back end is realized by adopting a Gin framework and Gorm is used as an ORM framework.
The consensus algorithm module realized at the back end calls different consensus algorithms through a plug-in technology of a Go language, the consensus algorithm to be tested needs to realize a Make method and a Start method, the Make method initializes consensus nodes, the Start method starts to run the consensus algorithms, and the nodes are subjected to message transmission through RPC remote process call, so that the number of RPC called among the nodes, the byte size of transmission messages, the time of each round of consensus operation and the result of each round of consensus operation can be conveniently obtained through simulated RPC, and data support is provided for performance analysis of the consensus algorithms.
And a network simulation module realized at the back end simulates RPC remote procedure call through the reflection technology of Go language and simulates a block chain network, a client and a consensus node. The attributes of network reliability, delay, delayed response and the like can be set through the simulated network, the connection condition of the client and the consensus node can be set through the simulated client, whether the consensus node is reliable, down and Byzantine behaviors can be set through the simulated consensus node, and the connection condition of the consensus node and the client and the connection condition of the consensus node and the consensus node can also be set.
The data acquisition module realized at the back end acquires the number of RPCs called between the consensus nodes and the byte size of a transmission message through a count variable and a byte variable in a network and consensus node structure, and acquires the time and the result of each consensus through a consensus _ time variable and a consensus _ result variable.
Step S2: and setting consensus algorithm parameters, network parameters, client parameters and consensus node parameters on a test and visual interface, and starting a performance test of the consensus algorithm.
During specific implementation, the front end and the back end communicate by adopting RESTful API, a GET request represents a search operation, a POST request represents an addition operation, a PUT request represents an editing operation, and a DELETE request represents a deletion operation. Meanwhile, Nginx is adopted for port forwarding and load balancing. The user can set the number of the consensus nodes, the client id, the master node id, the instruction sent by the client and the disconnection node id through an input box on a consensus algorithm testing and visualization interface, set the reliability, delay and delayed response of a network through a switch, set the running round number of the consensus algorithm through a counter, check whether the consensus nodes are available through a search button, click a submit button to start testing the consensus algorithm, and Nginx sends the parameters to the back end through a POST request.
Step S3: the back end configures the consensus algorithm module and the network simulation module according to corresponding parameters, and acquires relevant data during the running of the consensus algorithm through the data acquisition module.
During specific implementation, the network simulation module sets the reliability, delay and delay response attributes of the network through network parameters set by the front end, initializes the client through the set client id, and adds the client into the block chain network; the consensus algorithm module initializes the consensus nodes according to the set number of the consensus nodes, adds the consensus nodes into the block chain network, and sets the consensus nodes to be available; the network simulation module is connected with the client and the consensus node, is connected with the consensus node and the consensus node, and adds the RPC service provided by the consensus node to the Server; and the consensus algorithm module runs the consensus algorithm through the Start method of the consensus algorithm and executes the instruction sent by the client.
Further, referring to fig. 2, it is an architecture diagram of an RPC call provided in this embodiment.
The client 201 sends a request to a message channel of the blockchain network by a Call method, and waits for a reply response of the blockchain network. The block link network 202 monitors the message channel through select, and when receiving a request sent by the client, processes the request through processReq method. In the processReq method, the request is processed correspondingly according to whether the network set in step S2 is reliable, delayed and delayed response attributes, the request is sent to the consensus node specified in the request by the dispatch method, and the service 204 in the consensus node 203 is called. The consensus node receives a request sent by the blockchain network, and sends the request to a service specified in the request through a dispatch method. And after receiving the request, the service executes the request and returns an execution result reply to the consensus node. After receiving the reply, the consensus node responds the reply to the blockchain network, and after receiving the reply, the blockchain network responds the reply to the client. For a consensus node in a blockchain network, it is both a client and a server.
The data acquisition module acquires the number of RPCs called between the consensus nodes and the byte size of a transmission message through a count variable and a byte variable in a network and consensus node structure, acquires the time and the result of each round of consensus through a consensus _ time variable and a consensus _ result variable, and returns data to the front end through Nginx.
Step S4: dynamically rendering a consensus process and a Debug process on a test and visualization interface, and analyzing the throughput, the time delay and the fault tolerance of the consensus algorithm.
Fig. 3 is a schematic structural diagram of an implementation manner of the consensus algorithm testing and visualization interface provided in this embodiment.
During specific implementation, the front end receives data returned by the back end from the Nginx, a dynamic rendering consensus process and a Debug process are bidirectionally bound through data of the VUE, and meanwhile, throughput, delay and fault tolerance of a consensus algorithm are analyzed through the ECharts, wherein the column graph represents the number of RPCs called between nodes and the byte size of transmission messages between the nodes, and the broken line graph represents the throughput, the delay and the fault tolerance.
Further, referring to fig. 4, it is a schematic diagram of a consensus node state provided in this embodiment.
Step S5: and managing the test data on the test management interface, and comparing the test data on the test comparison interface.
Fig. 5 is a schematic structural diagram of an implementation manner of the consensus algorithm test management interface provided in this embodiment.
In specific implementation, a user can select the number of the test data displayed on each page, can click the page number below to directly jump to the corresponding page, and can also input the corresponding page number in the input box to jump to the page. Meanwhile, the user can edit data such as the name of the test, the throughput of the test, the time delay, the fault tolerance and the like through the edit button, and can delete corresponding test data through the delete button.
Fig. 6 is a schematic structural diagram of an implementation manner of the consensus algorithm test comparison interface provided in this embodiment.
In specific implementation, a user can select test data to be compared through a multi-selection box, can select the number of rounds to be compared through a counter, can compare the throughput, the delay and the fault tolerance of the consensus algorithm through a pull-down menu, and click a comparison button to compare different test data.
The above description is only a preferred embodiment of the present invention, and the scope of the present invention is not limited to the above embodiment, but equivalent modifications or changes made by those skilled in the art according to the present disclosure should be included in the scope of the present invention as set forth in the appended claims.
Claims (9)
1. A visual block chain consensus algorithm performance test method is characterized in that: the method comprises the following steps:
s1, establishing a consensus algorithm test and visualization interface, a test management interface and a test comparison interface at the front end, and establishing a consensus algorithm module, a network simulation module and a data acquisition module at the rear end;
s2, setting consensus algorithm parameters, network parameters, client parameters and consensus node parameters on a test and visualization interface, and starting a performance test of the consensus algorithm;
s3, configuring the consensus algorithm module and the network simulation module by the back end according to corresponding parameters, and collecting related data during the running of the consensus algorithm through the data collection module;
s4, dynamically rendering a consensus process and a Debug process on a test and visualization interface, and analyzing the throughput, the delay and the fault tolerance of the consensus algorithm;
and S5, managing the test data on the test management interface and comparing the test data on the test comparison interface.
2. The method according to claim 1, wherein the method comprises: the consensus algorithm parameters set by the test and visualization interface comprise the number of consensus nodes, the id of a main node and the number of rounds of running of the consensus algorithm, the network parameters comprise the reliability of the network, whether the network delays or not and whether the network delays response or not, the client parameters comprise the id of a client and an instruction sent by the client, and the consensus node parameters comprise the id of a node which a user wants to disconnect and the id of whether the node becomes a Byzantine node or not.
3. The method according to claim 1, wherein the method comprises: the testing and visualization interface represents different states of different nodes in the consensus process through different display modes, the client node, the main node and the common consensus node are respectively marked through different colors, and the timer of each node, the node being in the down state, the node being a Byzantine node, the node consensus being successful or the node consensus failing are respectively represented through different marks.
4. The method according to claim 1, wherein the method comprises: the testing and visualization interface analyzes the throughput, the delay and the fault tolerance of the consensus algorithm through the data acquired by the data acquisition module, and visualizes the throughput, the delay and the fault tolerance through the ECharts, wherein the column graph represents the number of RPCs called between the nodes and the byte size of the transmission messages between the nodes, and the broken line graph represents the throughput, the delay and the fault tolerance.
5. The method according to claim 1, wherein the method comprises: the consensus algorithm module is used for calling different consensus algorithms, initializing the consensus nodes according to the set consensus algorithm parameters, and operating the consensus algorithms according to the set consensus algorithm operating turns.
6. The method according to claim 1, wherein the method comprises: the network simulation module simulates RPC remote procedure calls through the reflection technology of Go language, simulates a block chain network and block chain nodes, sets network attributes such as network reliability, delay and delayed response through the simulated network, sets whether the block chain nodes are reliable or not through the simulated block chain nodes, and whether downtime or byzantine behaviors occur or not.
7. The method according to claim 1, wherein the method comprises: the data acquisition module acquires the number of RPC called between the consensus nodes, the byte size of transmission messages, the time of each round of consensus and the result of each round of consensus through related variables in the network and the consensus node structure body, and provides reference data for performance analysis of the consensus algorithm.
8. The method according to claim 1, wherein the method comprises: the test management interface is used for managing historical test data, displaying relevant data of each round of consensus algorithm operation on the page in a table form, and editing and deleting the data.
9. The method according to claim 1, wherein the method comprises: the test comparison interface is used for comparing historical test data, selecting the historical test data to be compared through a multi-selection frame, selecting the number of rounds to be compared through a counter, and selecting the performance index to be compared through a pull-down menu.
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