CN102857571B - Combined service simulation method and device thereof - Google Patents

Abstract

The present invention provides a combined service simulation method and device. The method includes: obtaining a combined service process model, which includes at least two function execution nodes and interaction modes of at least two function execution nodes; according to the combined service process The function indicators of each function execution node in the model generate the simulation atomic service set corresponding to each function execution node; determine the simulation corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to the preset algorithm Atomic service: Execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model; output the simulation execution result. The invention reduces the error rate of the formal execution of the combined service by simulating and executing the combined service, thereby reducing the cost of the combined service.

Description

Composite service simulation method and device

technical field

The invention relates to WEB application technology, in particular to a combined service simulation method and device.

Background technique

In recent years, with the rapid development of information technology and the Internet, the degree of informatization in various sectors of society is getting higher and higher. Therefore, Web services propose a service-oriented distributed computing model, namely composite services. Composing services is the process of combining multiple services into a new service to increase the functionality and performance of the service. If the combined target, related services and their interaction methods are known, you only need to find the corresponding service, create and execute the corresponding combined script.

However, after multiple services are combined, it is difficult to find the bottleneck in the actual execution process of the combined service. It may be found that the effect of the combined service is not satisfactory after many times of execution, and then modified, which will lead to Waste of time and money.

Contents of the invention

The purpose of the present invention is to provide a composite service simulation method and device to realize the simulation of composite services.

The first aspect of the present invention is to provide a composite service simulation method, including:

Acquiring a combined service process model, the combined service process model including at least two function execution nodes and the interaction modes of the at least two function execution nodes;

Generate a simulation atomic service set corresponding to each function execution node according to the function index of each function execution node in the combined service process model;

Determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm;

Execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model;

Output the simulation execution result.

Another aspect of the present invention is to provide a composite service simulation device, comprising:

A receiving module, configured to acquire a combined service process model, the combined service process model including at least two function execution nodes and an interaction mode of the at least two function execution nodes;

A simulation atomic service generation module, configured to generate a simulation atomic service set corresponding to each function execution node according to the function indicators of each function execution node in the combined service process model;

The simulation atomic service selection module is used to determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm;

A simulation execution module, configured to execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model;

The output module is used to output the simulation execution result.

The beneficial effect of adopting the above-mentioned technical solution of the present invention is: according to the interaction mode of at least two function execution nodes in the combined service process model, the simulated atomic service corresponding to each function execution node can be clearly known. Combining various performances of the service enables users to modify it when the performance of the combined service is not ideal, thereby reducing the error rate of the formal operation of the combined service, thereby reducing the cost of the combined service.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description These are some embodiments of the present invention. For those skilled in the art, other drawings can also be obtained according to these drawings without any creative effort.

Fig. 1 is the flow chart of the embodiment of the combined service simulation method of the present invention;

2 is a schematic diagram of Embodiment 1 in which a selection node selects a downstream function execution node in the combined service simulation method of the present invention;

3 is a schematic diagram of Embodiment 2 in which a selection node selects a downstream function execution node in the combined service simulation method of the present invention;

Fig. 4 is a schematic structural diagram of an embodiment of a combined service simulation device according to the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

Fig. 1 is a flow chart of an embodiment of the composite service simulation method of the present invention, as shown in Fig. 1, the composite service simulation method may include the following steps:

Step 101, obtaining a composite service process model, the composite service process model including at least two function execution nodes and the interaction modes of the at least two function execution nodes;

It should be noted that the execution subject of this embodiment may be a composite service simulation device. The composite service process model refers to a business process constructed by users according to expected service functions, including at least two function execution nodes and the interaction modes of the at least two function execution nodes. Users can directly import the existing business processes provided by the system into the simulation device, and can also customize the business processes of combined services. For example, users can use Hypertext Markup Language (Hypertext Markup Language 5 , referred to as HTML5) or the visual interface of the extensible development platform Eclipse plug-in to define the process. The definition process can be carried out in a drag-and-drop manner, or in other ways, such as Microsoft’s drawing software Visio, and at the same time give The node number of each function execution node in the process, the function index of each function execution node, the weight of the interaction mode of at least two function execution nodes, and other information.

Step 102, generating a simulated atomic service set corresponding to each function execution node according to the function index of each function execution node in the combined service process model;

In this embodiment, one or more simulation atomic services corresponding to the function indicators of each function execution node can be generated respectively according to the function indicators of each function execution node in the combined service process model, so as to form the simulation atoms corresponding to each function execution node In the service set, the function index of the function execution node may include the execution time of the function execution node, the execution cost information of the function execution node, the execution reliability information of the function execution node, and the like.

Step 103: Determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm;

Since there may be multiple simulation atomic services in the simulation atomic service set corresponding to the functional index of each function execution node, before each simulation, one simulation atomic service should be selected from each function execution node as the simulation atomic service for this simulation. Simulate atomic services. This selection process can be selected through a pre-written algorithm, and further, can also be selected according to a user's instruction.

Step 104, execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model;

In this embodiment, the interaction mode of the at least two function execution nodes includes the order of execution of each function execution node, logical relationship, etc. The simulated atomic service is used to simulate the composite service corresponding to the composite service process model.

Step 105, outputting the simulation execution result.

After the combined service is simulated according to the above steps, the simulation execution results can also be output, and the user can use the output simulation result data or use statistical and data mining methods to evaluate and further analyze the various performances of the combined service.

In the above-mentioned embodiment, the simulated atomic service corresponding to each function execution node is executed according to the interaction mode of at least two function execution nodes in the composite service process model, and the items of the composite service corresponding to the composite service process model can be clearly known Performance, so that users can modify it when the performance of the composite service is not ideal, thereby reducing the error rate of the formal execution of the composite service, thereby reducing the cost of the composite service.

Specifically, in the above embodiment, the generation of the simulated atomic service set corresponding to each function execution node according to the function indicators of each function execution node in the combined service process model may be:

Determine the attribute object of the simulation atomic service corresponding to the function execution node, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object according to the function index of the function execution node. In this embodiment, the attribute object of the simulated atomic service may include a time attribute, a cost attribute, and a reliability attribute of the simulated atomic service, wherein the time attribute refers to the time required to execute the simulated atomic service. In the time attribute, It also includes the upper limit and lower limit of the time required to execute the simulation atomic service and the distribution of the execution time, such as constant distribution or normal distribution.

The cost attribute refers to the cost of executing the simulation atomic service. In the cost attribute, it also includes the cost upper limit and cost lower limit of the cost of executing the simulation atomic service and the distribution of execution costs. For example, it can be a constant distribution or normal distribution, etc.

The reliability attribute refers to the reliability after the execution of the simulation atomic service. The reliability attribute also includes the upper limit and lower limit of the reliability of the execution of the simulation atomic service and the distribution of the execution reliability. For example, it can be a constant distribution or normal distribution, etc.

According to the attribute object of the simulation atomic service, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object, randomly generate at least one that contains the attribute object and each parameter in each attribute object is within the corresponding value range Simulating the atomic service, so that each attribute object satisfies a corresponding attribute distribution when the at least one simulated atomic service is executed.

For example, when a large number of simulation atomic services are to be generated on a function execution node, the service generator corresponding to the function execution node can be used to generate them. The service generator also includes time attributes, cost attributes and reliability attributes, each of which Attributes (i.e., time attribute, cost attribute, and reliability attribute) also include parameter 1, parameter 2, and distribution respectively. The time attribute is used as an example for illustration. In this embodiment, the distribution refers to multiple executions For the time distribution of the simulation atomic service, if the normal distribution is taken as an example, parameter 1 in the time attribute indicates the average value of the execution time of the simulation atomic service for multiple executions, and parameter 2 indicates the execution time of the simulation atomic service for multiple executions , and parameter 1 in the time attribute is bound with the parameter generator PGa to generate parameter 1 of the time attribute of the simulated atomic service, and parameter 2 in the time attribute is bound with the parameter generator PGb for Generate parameter 2 of the simulation atomic service time attribute. Assuming that three simulated atomic services are to be generated on a certain function execution node, first determine the distribution of the simulated atomic services to be generated according to the functional indicators of the function execution node. In this embodiment, the normal distribution is taken as an example for illustration; Then, according to the function index of the function execution node, specify the upper limit value and the lower limit value respectively for the parameter generator PGa and the parameter generator PGb, such as specifying the lower limit value 3 and the upper limit value 5 for the parameter generator PGa, then Indicates that the parameter 1 in the time attribute of the simulation atom service to be generated is in the range of 3 to 5; when the lower limit value of the parameter generator PGb is specified as 1 and the upper limit value is 2, it means the simulation atom to be generated Parameter 2 in the time attribute of the service is in the range 1 to 2. If three simulated atomic services, namely S1, S2, and S3 are generated respectively according to the upper and lower limits specified by the parameter generator PGa and parameter generator PGb above, and parameter generator PGa generates parameters 1 of S1, S2, and S3 respectively are 3.2, 4.1, and 4.7, and parameter generator PGb generates parameters 2 of S1, S2, and S3 as 1.1, 1.3, and 1.7 respectively. Therefore, when the simulation atomic service S1 is executed multiple times, its execution time is shown as 3.2 as the average value, 1.1 is a normal distribution of variance. When the simulation atomic service S2 is executed multiple times, its execution time is shown as a normal distribution with a mean value of 4.1 and a variance of 1.3. When the simulation atomic service S3 is executed multiple times, its execution time performance is It is a normal distribution with a mean of 4.7 and a variance of 1.7.

In this embodiment, the constant distribution is taken as an example to illustrate the generation of the cost attribute parameters of the simulation atomic service according to the function index of the function execution node. Since only one parameter is needed in the constant distribution, it means that the execution of the simulated atomic service to be generated is Therefore, in this embodiment, only one parameter needs to be generated. Similar to the above embodiment, the parameter of the consumption attribute is also generated by the parameter generator bound to it. If the parameter generator bound to the parameter of the consumption property is the parameter generator PGc, specify the upper limit value and the lower limit value of the parameter generator PGc according to the function index of the function execution node, such as specifying the lower limit value of the parameter generator PGc is 10, and the upper limit value is 15. According to the range specified by the parameter generator PGc, the parameters of the consumption attributes of three simulated atomic services S1, S2, and S3 are 11.2, 13.3, and 14.7, which means that the simulated atomic service S1 is executed each time. The execution cost of each simulation atomic service S2 is 11.2, the execution cost of each simulation atomic service S2 is 13.3, and the execution cost of each simulation atomic service S3 is 14.7.

Similarly, the reliability attribute parameters of the simulated atomic service may also be generated according to the above-mentioned generation method of the time attribute parameter or the cost attribute parameter, which will not be repeated here.

When generating a simulated atomic service based on an existing atomic service, the time attribute parameters, cost attribute parameters, and reliability attribute parameters of the existing atomic service can be directly used as the time attribute parameters, cost attribute parameters, and reliability of the simulated atomic service. property parameters, and use the distribution properties of the existing atomic services as the distribution properties of the simulated atomic services. These parameter values can be provided by the service provider or obtained through the execution logs of the existing atomic services.

Further, in the above embodiment, the determination of the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm may be:

According to a preset algorithm, the simulation atomic service corresponding to each function execution node in this simulation is jointly determined from the simulation atomic service set corresponding to each function execution node; specifically, for example, the set algorithm is such that the cost of executing this simulation is less than 400 yuan. Therefore, when selecting the simulation atomic service corresponding to the function execution node, the cost of the simulation atomic service needs to be considered, and the total cost of the simulation atomic service corresponding to each function execution node also needs to be considered, rather than simply considering the execution The consumption of the simulated atomic service of a function execution node. For another example, when there are two function execution nodes A and B executing in parallel, if it is already known that the execution time of function execution node B will be very long (longer than A), then it should not be used when selecting the simulation atomic service of function execution node A Consider optimizing the execution time of function execution node A, but should consider some other quality of service attributes, such as execution cost, etc.; this method is based on the overall service quality of composite services, so it has certain advantages in service quality ;

It may also be: respectively determine the simulation atomic service corresponding to each function execution node according to each preset algorithm corresponding to each function execution node. Specifically, different algorithms are configured on each function execution node, so that corresponding simulation atomic services are independently selected from each function execution node according to the algorithm configured on each function execution node. Because this method regards each function execution node as an independent execution node, and the algorithm for setting up a single function execution node is usually relatively simple, therefore, using this method to select the simulation atomic service corresponding to each function execution node usually costs The time is shorter.

In actual application, any one of the above methods can be selected according to requirements to select the simulation atomic service corresponding to the function execution node.

Further, in the above embodiment, the combined service process model may further include a selection node, the selection node is used to select one or more of the downstream function execution nodes of the one function execution node after one function execution node. multiple; the execution of the simulated atomic service corresponding to each function execution node according to the interactive mode of at least two function execution nodes in the combined service process model specifically includes:

After executing the one function execution node, the selection node generates a random number within a preset range, and selects the downstream function execution according to the random number and the preset weight upper limit and weight lower limit of each downstream function execution node One or more of the nodes, if the random number is within the range defined by the weight lower limit and weight upper limit of a downstream function execution node, then select the downstream function execution node, if the random number is in multiple downstream function execution nodes Within the range defined by the weight lower limit and weight upper limit, select the plurality of downstream function execution nodes; after executing the selection node, execute one or more of the downstream function execution nodes selected by the selection node.

For example, FIG. 2 is a schematic diagram of Embodiment 1 in which a selection node selects a downstream function execution node in the combined service simulation method of the present invention. As shown in FIG. 2 , the lower limit of the weight of the first downstream function execution node 203 of the selection node 202 is 0, and the weight The upper limit is 50, and the lower limit of the weight of the second downstream function execution node 204 of the selected node 202 is 50, and the upper limit of the weight is 100. During the simulation execution process, after the upstream function execution node 201 of the selected node 202 is executed, the selected node 202 is executed. , the random number between 0 and 100 is generated by the selection node 202. Therefore, the probability that the first downstream function execution node 203 and the second downstream function execution node 204 of the selection node 202 are selected are respectively 50%. If the selection node 202 generates The random number is 60, because the random number 60 is within the range defined by the weight lower limit 50 and the weight upper limit 100 of the second downstream function execution node 204 of the selection node 202, therefore, after the selection node 202 is executed, the selection node 202 The second downstream function execution node 204 is selected for execution.

FIG. 3 is a schematic diagram of Embodiment 2 in which a selection node selects a downstream function execution node in the combined service simulation method of the present invention. As shown in FIG. 3 , the lower limit of the weight of the first downstream function execution node 203 of the selection node 202 is 0, and the upper limit of the weight is 100, and the lower limit of the weight of the second downstream function execution node 204 of the selected node 202 is 0, and the upper limit of the weight is 100. During the simulation execution process, after the upstream function execution node 201 of the selected node 202 is executed, the selected node 202 is executed, by The selection node 202 generates a random number between 0 and 100. Therefore, the probability that the first downstream function execution node 203 and the second downstream function execution node 204 of the selection node 202 are selected is 100%, since the selection node 202 may generate 0 Any random number between 100 and 100, and because the random numbers within this range are all within the range defined by the weight lower limit 0 and the weight upper limit 100 of the first downstream function execution node 203 and the second downstream function execution node 204 of the selection node 202 , therefore, after the selection node 202 is executed, the first downstream function execution node 203 and the second downstream function execution node 204 are executed in parallel.

Preferably, when performing the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model, it may also include:

The execution process is monitored, and monitoring information is generated, and the monitoring information may include the overall service quality information of the combined service and the service quality information of each function execution node in the combined service process model. In this embodiment, the overall service quality information of the composite service may be the overall execution time information, cost information, and reliability information of the composite service; the service quality information of each function execution node in the composite service process model may be The execution time information, cost information and reliability information of each function execution node in the combined service process model. Furthermore, the above monitoring information can also be output as a simulation execution result, so that the user can use the output simulation execution result data or use statistical and data mining methods to evaluate and further analyze various performances of the composite service.

Fig. 4 is a schematic structural diagram of an embodiment of a composite service simulation device according to the present invention. As shown in Fig. 4, the composite service simulation device may include:

The receiving module 401 is configured to acquire a combined service process model, the combined service process model including at least two function execution nodes and the interaction modes of the at least two function execution nodes;

A simulation atomic service generation module 402, configured to generate a simulation atomic service set corresponding to each function execution node according to the function indicators of each function execution node in the combined service process model;

The simulation atomic service selection module 403 is used to determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm;

The simulation execution module 404 is configured to execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model;

An output module 405, configured to output simulation execution results.

Further, the simulation atomic service generating module 402 may include:

The simulation atomic service parameter determination unit 406 is configured to determine the attribute object of the simulation atomic service corresponding to the function execution node, the attribute distribution of each attribute object, and the value of each parameter in each attribute object according to the function index of the function execution node scope;

The simulation atomic service generation unit 407 is used to randomly generate the attribute object containing the attribute object and each parameter in each attribute object according to the attribute object of the simulation atomic service, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object. At least one simulated atomic service within a corresponding value range, so that each attribute object satisfies a corresponding attribute distribution when the at least one simulated atomic service is executed.

Further, the simulation atomic service selection module 403 can be specifically used for:

Jointly determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm; or, according to each preset algorithm corresponding to each function execution node respectively Determine the simulation atomic service corresponding to the function execution node.

Preferably, the combined service process model further includes a selection node, the selection node is used to select one or more downstream function execution nodes of the one function execution node after one function execution node;

The simulation execution module 404 may include:

a function execution node execution unit 408, configured to execute the one function execution node;

A selection node execution unit 409, configured to execute the selection node after the function execution node execution unit 408 executes the one function execution node;

The function execution node execution unit 408 is further configured to execute one or more of the downstream function execution nodes selected by the selection node after the selection node execution unit 409 executes the selection node.

Further, the selecting node execution unit 409 may also include:

A random number generation subunit 410, configured to generate a random number within a preset range;

The downstream function execution node selection subunit 411 is configured to select one or more of the downstream function execution nodes according to the random number and the preset weight value of each downstream function execution node.

Specifically, the preset weight value includes a weight lower limit and a weight upper limit, and the downstream function execution node selection subunit 411 can also be specifically configured to:

If the random number is within the range defined by the lower weight limit and upper weight limit of a downstream function execution node, the one downstream function execution node is selected.

Further, the combined service simulation device may also include:

A monitoring module 412, configured to monitor the execution process and generate monitoring information, where the monitoring information includes the overall service quality information of the combined service and the service quality information of each function execution node in the combined service process model;

Specifically, the output module 405 may also be configured to: output the monitoring information.

The atomic service simulation device of this embodiment can be used to execute the technical solution of the method embodiment shown in FIG. 1 , and its implementation principle and technical effect are similar, and will not be repeated here.

Those of ordinary skill in the art can understand that all or part of the steps for implementing the above method embodiments can be completed by program instructions and related hardware. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above-mentioned method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other various media that can store program codes.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the various embodiments of the present invention. scope.

Claims (9)

1. A combined service simulation method, characterized in that, comprising: Acquiring a combined service process model, the combined service process model including at least two function execution nodes and the interaction modes of the at least two function execution nodes; Generate a simulation atomic service set corresponding to each function execution node according to the function index of each function execution node in the combined service process model; Determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm; Execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model; Output simulation execution results; According to the function index of each function execution node in the combined service process model, the simulation atomic service set corresponding to each function execution node is generated, specifically: Determine the attribute object of the simulation atomic service corresponding to the function execution node, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object according to the function index of the function execution node; and According to the attribute object of the simulation atomic service, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object, randomly generate at least one that contains the attribute object and each parameter in each attribute object is within the corresponding value range Simulating the atomic service, so that each attribute object satisfies a corresponding attribute distribution when the at least one simulated atomic service is executed. 2. The method according to claim 1, characterized in that, according to the preset algorithm, the simulation atomic service corresponding to each function execution node in this simulation is determined from the simulation atomic service set corresponding to each function execution node, specifically for: Jointly determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm; or, according to each preset algorithm corresponding to each function execution node respectively Determine the simulation atomic service corresponding to the function execution node. 3. The method according to claim 1, wherein the combined service process model further includes a selection node, the selection node is used to select the downstream function execution of the one function execution node after a function execution node one or more of the nodes; Executing the simulated atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model specifically includes: After executing the one function execution node, execute the selection node; After the selection node is executed, one or more of the downstream function execution nodes selected by the selection node are executed. 4. The method according to claim 3, wherein the execution of the selected node is specifically: Generate random numbers within a preset range; One or more of the downstream function execution nodes are selected according to the random number and the preset weight value of each downstream function execution node. 5. The method according to claim 4, wherein the preset weight value includes a weight lower limit and a weight upper limit; and according to the random number and the preset weight value of each downstream function execution node, the selected One or more of the downstream function execution nodes, specifically: If the random number is within the range defined by the lower weight limit and upper weight limit of a downstream function execution node, the one downstream function execution node is selected. 6. The method according to any one of claims 1-5, characterized in that, when performing the simulation atomic service corresponding to each function execution node according to the interactive mode of at least two function execution nodes in the combined service process model ,Also includes: monitoring the execution process, and generating monitoring information, the monitoring information including the overall service quality information of the combined service and the service quality information of each function execution node in the combined service process model; The output simulation execution results are specifically: Output the monitoring information. 7. A combined service simulation device, characterized in that it comprises: A receiving module, configured to acquire a combined service process model, the combined service process model including at least two function execution nodes and an interaction mode of the at least two function execution nodes; A simulation atomic service generation module, configured to generate a simulation atomic service set corresponding to each function execution node according to the function indicators of each function execution node in the combined service process model; The simulation atomic service selection module is used to determine the simulation atomic service corresponding to each function execution node in this simulation from the simulation atomic service set corresponding to each function execution node according to a preset algorithm; A simulation execution module, configured to execute the simulation atomic service corresponding to each function execution node according to the interaction mode of at least two function execution nodes in the combined service process model; An output module, configured to output simulation execution results; The simulation atomic service generation module includes: The simulation atomic service parameter determination unit is used to determine the attribute object of the simulation atomic service corresponding to the function execution node, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object according to the function index of the function execution node ; The simulation atomic service generation unit is used to randomly generate the attribute object containing the attribute object and each parameter in each attribute object according to the attribute object of the simulation atomic service, the attribute distribution of each attribute object, and the value range of each parameter in each attribute object. At least one simulated atomic service within a corresponding value range, so that each attribute object satisfies a corresponding attribute distribution when the at least one simulated atomic service is executed. 8. The device according to claim 7, wherein the combined service process model further includes: a selection node, the selection node is used to select one or more of the downstream function execution nodes of the one function execution node after one function execution node; The simulation execution module includes: a function execution node execution unit, configured to execute the one function execution node; Select a node execution unit, the selection node execution unit includes: a random number generation subunit, used to generate a random number within a preset range; a downstream function execution node selection subunit, used to execute according to the random number and each downstream function The preset weight value of the node, select one or more of the downstream function execution nodes; The function execution node execution unit is further configured to execute one or more of the downstream function execution nodes selected by the selection node after the selection node execution unit executes the selection node. 9. The device according to claim 7 or 8, characterized in that the device further comprises: A monitoring module, configured to monitor the execution process and generate monitoring information, the monitoring information including the overall service quality information of the combined service and the service quality information of each function execution node in the combined service process model; The output module is specifically configured to: output the monitoring information.