CN113923146B - Visual block chain consensus algorithm performance test method - Google Patents
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Abstract
A visual block chain consensus algorithm performance test method comprises the steps of establishing a consensus algorithm test and visual interface, a test management interface and a test comparison interface at the front end, and realizing a consensus algorithm module, a network simulation module and a data acquisition module at the rear end; setting parameters of a consensus algorithm, network parameters, client parameters and parameters of a consensus node in a testing and visualization interface, and starting performance testing of the consensus algorithm; the rear end configures a consensus algorithm module and a network simulation module according to the corresponding parameters, and collects operation related data through a data collection module; dynamically rendering consensus and Debug processes on a testing and visualization interface, and analyzing throughput, delay and fault tolerance; and managing the test data at a test management interface and comparing the test data at a test comparison interface. The method has the advantages of simplicity, intuitiveness and visualization, reduces the learning difficulty, improves the learning efficiency and improves the user experience; by adopting a front-end and rear-end separation development mode, new functions can be conveniently added, and the method has good expansibility.
Description
Technical Field
The invention relates to the field of blockchain, in particular to a performance test method of a visual blockchain consensus algorithm.
Background
The consensus algorithm is a core element of the blockchain technology and solves the problem of mutual trust between distributed network nodes. At the same time, consensus algorithms are also a hotspot in distributed system research in recent years.
Currently, the research of consensus algorithms is limited by many factors. For researchers of the consensus algorithm, the problems of communication between nodes, node deployment, cryptography and the like are required to be processed while the consensus algorithm is designed and realized. The test consensus algorithm also needs a large number of nodes to perform performance test, meanwhile, the network reliability, delay and other attributes are difficult to set, the downtime and the Bayesian behavior of the nodes are also lacking, and the communication data between the nodes is also lacking to perform performance analysis on the consensus algorithm. For learners of the consensus algorithm, specific implementation of different consensus algorithms is needed to be known, but different consensus algorithms are often implemented by different programming languages, so that the learning difficulty of the consensus algorithm is greatly improved. Therefore, in order to improve the research efficiency of the consensus algorithm researchers and to reduce the learning difficulty of the consensus algorithm learners, the performance test method and system of the block chain consensus algorithm are introduced.
The existing block chain consensus algorithm performance test schemes are not many, and have the advantages of adopting real nodes for testing, adopting intermediate nodes for testing, adopting dockers for testing, adopting command lines for visualization, adopting computer resources occupied in the running process of the consensus algorithm for performance analysis and the like. These schemes have several problems: firstly, the testing mode is complex, the deployment of a testing system is complex, and meanwhile, the parameters of the testing system are difficult to configure; secondly, the performance analysis of the consensus algorithm is not strict enough, and the data analysis under the conditions of unreliable network, network delay, downtime of the consensus node, barking behavior of the consensus node and the like is lacking; thirdly, most test systems only perform performance test on the consensus algorithm of the Ethernet and HYPERLEDGER FABRIC, namely perform performance test on the consensus algorithm of the PoW and PBFT, and cannot test the consensus algorithm realized by researchers, so that the universality is not enough; finally, the 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, which aims to solve the problems that the block chain consensus algorithm test mode is complex, the deployment of a test system is complex, the parameters of the test system are difficult to configure, the performance analysis of the consensus algorithm is not strict enough, the test object is single, the universality is insufficient, the visualization of the consensus process is not simple and 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 parameters of a consensus algorithm, network parameters, client parameters and parameters of a consensus node in a testing and visual interface, and starting performance testing of the consensus algorithm;
S3, the rear end configures a consensus algorithm module and a network simulation module according to corresponding parameters, and relevant data of the consensus algorithm during operation is acquired through a data acquisition module;
S4, dynamically rendering a consensus process and a Debug process on a testing and visualization interface, and analyzing throughput, delay and fault tolerance of a consensus algorithm;
S5, managing test data in a test management interface, and comparing the test data in a test comparison interface.
Further, the parameters of the consensus algorithm set by the test and visualization interface comprise the number of consensus nodes, the id of a main node and the running number of the consensus algorithm, the network parameters comprise the reliability of the network, whether the network delays to respond, the client parameters comprise the client id and the instruction sent by the client, and the parameters of the consensus nodes comprise the id of the node which the user wants to disconnect and the id of the node which becomes the Bayesian node.
Further, the test and visualization interface indicates different states of different nodes in the consensus process through different display modes, marks the client node, the main node and the common consensus node through different colors, and indicates a timer and a node of each node to be in a downtime state through different identifications, wherein the node is a Bayesian node, the node consensus success or the node consensus failure.
Further, the test and visualization interface analyzes throughput, delay and fault tolerance of a consensus algorithm through data collected by the data collection module, and visualizes the throughput, delay and fault tolerance through ECharts, wherein a bar graph represents the number of RPCs called between nodes and the byte size of a transmission message between the nodes, and a line graph represents the throughput, delay and fault tolerance.
Further, the consensus algorithm module is used for calling different consensus algorithms, initializing the consensus nodes according to the set parameters of the consensus algorithm, and running the consensus algorithm according to the set running round number of the consensus algorithm.
Further, the network simulation module simulates RPC remote procedure call through the reflection technology of Go language, simulates a blockchain network and blockchain nodes, sets network attributes such as network reliability, delay and delay response through the simulated network, and sets whether the blockchain link points are reliable, whether downtime and camping occur or not through the simulated blockchain nodes.
Further, the data acquisition module acquires the number of RPCs called between the consensus nodes, the byte size of the 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 body, and provides reference data for the performance analysis of the consensus algorithm.
Further, the test management interface is used for managing historical test data, displaying relevant data operated by each round of consensus algorithm on the page in a table form, and editing and deleting the data.
Further, the test comparison interface is used for comparing historical test data, selecting the historical test data to be compared through a plurality of boxes, selecting the number of rounds to be compared through a counter, and selecting the performance index to be compared through a pull-down menu.
The beneficial effects of the invention are as follows:
The visual block chain consensus algorithm performance test method provided by the invention provides a universal, simple and visual test scheme which is easy to deploy and configure for the block chain consensus algorithm performance test, 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. For a consensus algorithm researcher, parameters related to the consensus algorithm, a network, a client and a consensus node can be allocated at the front end, the self consensus algorithm is improved through visualized 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 flow of the node. For the learners of the consensus algorithm, the technical scheme provided by the invention has the advantages of simplicity, intuitiveness 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 front-end and rear-end separation, can conveniently add new functions, and has good expansibility.
Drawings
FIG. 1 is a schematic diagram of a method for testing performance of a visual block chain consensus algorithm according to an embodiment of the present invention.
FIG. 2 is a diagram of an architecture for an RPC call provided in an embodiment of the invention.
FIG. 3 is a schematic diagram of an implementation of a consensus algorithm test and visualization interface provided in an 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 diagram of an implementation of a consensus algorithm test management interface provided in an embodiment of the present invention.
FIG. 6 is a schematic diagram of one implementation of a consensus algorithm test comparison interface provided in an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the attached drawings.
Referring to fig. 1, a schematic diagram of a performance testing method of a visual block chain consensus algorithm is provided in this embodiment.
Specifically, the architecture of the visual blockchain consensus algorithm performance testing method provided in the present embodiment includes: a user layer, a consensus layer, a visualization layer, a network layer, and a data layer.
Preferably, the user layer 101 is configured to set a consensus algorithm, 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 ids and master node ids; the network setting module can set whether the network is reliable, whether the network is delayed and whether the network is delayed for responding; 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 consensus node setting module can select the node to disconnect, simulate the downtime and the Bayesian and the horrible behaviors of the node, and can check whether a certain node is available. The performance analysis module of the consensus algorithm carries out line graph analysis on throughput, delay and fault tolerance of the consensus algorithm through ECharts, and displays the number of RPCs called among nodes in the consensus process and the byte size of a transmitted message through a histogram. The test management module is mainly used for editing and deleting the historical test data. The test comparison module can compare the 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 algorithm realizes a Make and Start method to test the own consensus algorithm, initialize a consensus node through the Make method, and run the consensus algorithm through the Start method.
Preferably, the visualization layer 103 is used for visualizing the consensus process and visualizing the Debug, and the front end acquires the data related to the consensus algorithm sent by the back end, and dynamically renders the consensus process and the Debug through the VUE.
Preferably, the network layer 104 is configured to emulate 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, whether the network is delayed or not for responding, maps the name of the client and the client structure body, the name of the consensus node and the consensus node structure body through the map, maps the situation that whether the consensus node and the consensus node are available or not, the connection situation of the client and the consensus node and the connection situation of the consensus node and the consensus node at the same time, receives a request sent by the client through a channel, processes the request correspondingly, and receives an instruction for closing the network through the channel. The RPC management module simulates RPC remote procedure Call through a reflection mechanism of the Go language, a Call method and a dispatch method are realized, a client and a consensus node Call the process of a target node through the Call method, and the target node processes a 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 may add a consensus node, delete a consensus node, determine whether a consensus node is available, add a service of a consensus node.
Preferably, the data layer 105 is configured to obtain the number of RPCs invoked between nodes during running of the consensus algorithm, the byte size of the transmission message, the time of each round of consensus running, and the result of each round of consensus running, and send these data to the front end for visualization processing and performance analysis of the consensus algorithm.
The visual block chain consensus algorithm performance test method provided by the embodiment mainly comprises the following steps S1 to S5:
Step S1: and a consensus algorithm testing and visualizing interface, a testing management interface and a testing 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.
In the step, the front end adopts VUE framework development, a consensus algorithm test and visualization interface, a test management interface and a test comparison interface are quickly constructed by adopting an Element UI, and ECharts is adopted for data visualization; the back end is realized by adopting a Gin framework and Gorm is adopted as an ORM framework.
The common-recognition algorithm module realized at the back end calls different common-recognition algorithms through the plug-in technology of the Go language, the common-recognition algorithm to be tested needs to realize a Make method and a Start method, the Make method initializes the common-recognition nodes, the Start method starts to operate the common-recognition algorithm, and message transmission is carried out among the nodes through RPC remote procedure call, so that the number of RPCs called among the nodes, the byte size of transmitted messages, the time of each round of common-recognition operation and the result of each round of common-recognition operation can be conveniently obtained through the simulated RPC, and the data support is provided for the performance analysis of the common-recognition algorithm.
The network simulation module realized by the back end simulates RPC remote procedure call through the reflection technology of Go language, and simulates a blockchain network, a client and a consensus node. The network reliability, delay response and other attributes 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 camping 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 the transmission message through a count variable and a byte variable in a network and the consensus node structure body, and acquires the time and the result of each round of consensus through a consensus _time variable and a consensus _result variable.
Step S2: setting parameters of a consensus algorithm, network parameters, client parameters and parameters of a consensus node at a testing and visualization interface, and starting performance testing of the consensus algorithm.
In specific implementation, the front end and the back end communicate by RESTfulAPI, the GET request represents a search operation, the POST request represents an addition operation, the PUT request represents an editing operation, and the DELETE request represents a deletion operation. Simultaneously, 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 instructions sent by the client and the disconnected node id through an input box on a consensus algorithm test and visualization interface, set the reliability, delay and delay response of a network through a switch, set the running number of the consensus algorithm through a counter, check whether the consensus nodes are available through a search button, click a submit button, start to test the consensus algorithm, and send the parameters to the back end through a POST request by Nginx.
Step S3: the back end configures a consensus algorithm module and a network simulation module according to the corresponding parameters, and collects related data of the consensus algorithm during operation through a data collection module.
In the specific implementation, the network simulation module sets the reliable, delay and delay response attribute of the network through the network parameters set by the front end, initializes the client through the set client id and adds the client into the blockchain network; the common-knowledge algorithm module initializes the common-knowledge nodes through the set number of the common-knowledge nodes, adds the common-knowledge nodes into the block chain network, and sets the common-knowledge nodes as available; the network simulation module is connected with the client and the consensus node, and is connected with the consensus node and the consensus node, and RPC service provided by the consensus node is added to the Server; and the consensus algorithm module runs the consensus algorithm through a Start method of the consensus algorithm, and executes the instruction sent by the client.
Further, referring to fig. 2, an architecture diagram of an RPC call is provided in this embodiment.
The client 201 sends a request to a message channel of the blockchain network through a Call method and waits for a reply response of the blockchain network. Blockchain network 202 listens to the message channel through select and when a request sent by a client is received, the request is processed through processReq. In the processReq method, according to whether the network set in the step S2 is reliable, delay, and delay response attribute, the request is processed correspondingly, and the request is sent to the consensus node designated in the request by the dispatch method, and the service 204 in the consensus node 203 is invoked. The consensus node receives a request sent by the blockchain network and sends the request to a service appointed in the request through a dispatch method. After receiving the request, the service executes the request and returns the execution result reply to the consensus node. The consensus node receives the reply and then sends the reply to the blockchain network, and the blockchain network receives the reply and then sends 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 the transmission message through a count variable and a byte variable in the network and the 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 the data to the front end through Nginx.
Step S4: and dynamically rendering a consensus process and a Debug process on a test and visualization interface, and analyzing throughput, delay and fault tolerance of a consensus algorithm.
Referring to fig. 3, a schematic structural diagram of an implementation manner of the consensus algorithm testing and visualization interface provided in the present embodiment is shown.
In the implementation, the front end receives data returned by the back end from the Nginx, dynamically renders a consensus process and a Debug process through data bidirectional binding of the VUE, and simultaneously analyzes throughput, delay and fault tolerance of a consensus algorithm through ECharts, wherein a bar graph represents the number of RPCs called among nodes and the byte size of a transmission message among the nodes, and a line graph represents the throughput, delay and fault tolerance.
Further, referring to fig. 4, a schematic diagram of a common node state is provided in this embodiment.
A circle 401 with a color #5793f3 represents a client node, a circle 402 with a color # d14a61 represents a master node, a circle 403 with a color #39b3e3 represents a common consensus node, a circle 404 represents a timer of each node through a display mode with different scales of pie charts, a circle 405 represents that the node is in a downtime state, or the node is a bayer node, a circle 406 represents that the node consensus is successful, and a circle 407 represents that the node consensus fails.
Step S5: and managing the test data at a test management interface and comparing the test data at a test comparison interface.
Referring to fig. 5, a schematic structural diagram of an implementation manner of the consensus algorithm test management interface provided in the present embodiment is shown.
In the implementation, the user can select the number of the test data displayed on each page, and can click the page number below to directly jump to the corresponding page, or can input the corresponding page number in the input box to carry out page jumping. Meanwhile, the user can edit the data such as the name of the test, the throughput, the delay, the fault tolerance and the like of the test through the editing button, and can delete the corresponding test data through the deleting button.
Referring to fig. 6, a schematic structural diagram of an implementation manner of the test comparison interface of the consensus algorithm according to the present embodiment is provided.
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 also compare throughput, delay and fault tolerance of a consensus algorithm through a pull-down menu, and can click a comparison button to compare different test data.
The above description is merely of preferred embodiments of the present invention, and the scope of the present invention is not limited to the above embodiments, but all equivalent modifications or variations according to the present disclosure will be within the scope of the claims.
Claims (6)
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 parameters of a consensus algorithm, network parameters, client parameters and parameters of a consensus node in a testing and visual interface, and starting performance testing of the consensus algorithm;
The parameters of the consensus algorithm set by the test and visualization interface comprise the number of consensus nodes, the id of a main node and the running number of the consensus algorithm, the network parameters comprise the reliability of the network, whether the network delays and whether the network delays the response, the client parameters comprise the client id and the instruction sent by the client, and the parameters of the consensus nodes comprise the id of the node which the user wants to disconnect and the id of the node which becomes a Bayesian node;
S3, the rear end configures a consensus algorithm module and a network simulation module according to corresponding parameters, and relevant data of the consensus algorithm during operation is acquired through a data acquisition module;
The test and visualization interface shows different states of different nodes in the consensus process in different display modes, marks the client node, the main node and the common consensus node respectively in different colors, and shows the timer and the node of each node in a downtime state, shows that the node is a Bayesian node, the node consensus is successful or the node consensus fails respectively in different identifications;
S4, dynamically rendering a consensus process and a Debug process on a testing and visualization interface, and analyzing throughput, delay and fault tolerance of a consensus algorithm;
The test and visualization interface analyzes throughput, delay and fault tolerance of a consensus algorithm through data acquired by the data acquisition module, and visualizes the throughput, delay and fault tolerance through ECharts, wherein a bar graph represents the number of RPCs called among nodes and the byte size of a transmission message among the nodes, and a line graph represents the throughput, delay and fault tolerance;
S5, managing test data in a test management interface, and comparing the test data in a test comparison interface.
2. The method for testing the performance of the visual block chain consensus algorithm according to claim 1, wherein the method comprises the following steps: the consensus algorithm module is used for calling different consensus algorithms, initializing the consensus nodes according to the set parameters of the consensus algorithm, and running the consensus algorithm according to the set running round number of the consensus algorithm.
3. The method for testing the performance of the visual block chain consensus algorithm according to claim 1, wherein the method comprises the following steps: the network simulation module simulates RPC remote procedure call by the reflection technology of Go language, simulates a blockchain network and blockchain nodes, sets network attributes such as network reliability, delay and delay response by the simulated network, and sets whether the blockchain link points are reliable, whether downtime and Bayesian behavior occur by the simulated blockchain nodes.
4. The method for testing the performance of the visual block chain consensus algorithm according to claim 1, wherein the method comprises the following steps: the data acquisition module acquires the number of RPCs called among the consensus nodes, the byte size of the 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 body, and provides reference data for the performance analysis of the consensus algorithm.
5. The method for testing the performance of the visual block chain consensus algorithm according to claim 1, wherein the method comprises the following steps: the test management interface is used for managing historical test data, displaying related data operated by each round of consensus algorithm in a table form on the page, and editing and deleting the data.
6. The method for testing the performance of the visual block chain consensus algorithm according to claim 1, wherein the method comprises the following steps: the test comparison interface is used for comparing historical test data, selecting the historical test data to be compared through a multi-selection box, 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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| Title |
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| 基于私有区块链的共识算法性能分析;庄海燕;;滨州学院学报(02);全文 * |
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| CN113923146A (en) | 2022-01-11 |
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