Cloud computing workflow scheduling method based on time cost and credibility constraint

Abstract

The invention relates to the technical field of cloud computing, in particular to a cloud computing workflow scheduling method based on time cost and credibility constraint, a computer readable storage medium and a computer program product. The cloud computing workflow scheduling method provided by the invention comprises the following steps: acquiring a target workflow, and identifying each task in the target workflow; the task execution credibility of each service provider is obtained, the time cost of each service provider for executing each task in the target workflow is obtained, and the time cost comprises the task transmission time cost and the task execution time cost; and according to the time cost and the credibility of each service provider, matching the target service provider of each task, so that the total execution time cost of the target workflow in the credible environment is lowest. According to the method, the credibility and the time cost of the service providers are comprehensively evaluated, and the execution service providers of each task in the target workflow are reasonably matched, so that each task can be efficiently executed in a credible environment.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing technology, and in particular to a cloud computing workflow scheduling method based on time cost and credibility constraints, a computer-readable storage medium, and a computer program product. Background Art

[0002] With the rapid development of cloud computing technology, enterprises and organizations have migrated their businesses and applications to cloud platforms to take advantage of the efficiency and flexibility of cloud computing. However, in a multi-service provider environment, how to reasonably allocate and schedule tasks to ensure that tasks meet security and reliability requirements while being executed efficiently has become an important challenge in cloud computing work scheduling. In particular, in scenarios involving sensitive data and critical businesses, it is crucial to choose a trustworthy service provider to perform tasks.

[0003] Existing cloud computing work scheduling methods mainly focus on the time cost of task execution, but often ignore the credibility assessment of service providers, resulting in tasks being assigned to unreliable service providers, increasing the risk of task failure. In addition, traditional methods have deficiencies in handling task dependencies and dynamic scheduling, and cannot fully optimize overall execution efficiency and resource utilization. These defects will lead to uncertainty and inefficiency in task execution in practical applications, restricting the widespread application of cloud computing. Summary of the invention

[0004] In view of the deficiencies of the prior art and the needs of practical applications, the present invention provides a cloud computing workflow scheduling method based on time cost and credibility constraints, a computer-readable storage medium, and a computer program product, which aims to reasonably match the execution service provider of each task in the target workflow by comprehensively evaluating the credibility and time cost of the service provider, so as to ensure that each task is efficiently executed in a trusted environment.

[0005] In the first aspect, the cloud computing workflow scheduling method based on time cost and credibility constraints provided by the present invention is characterized in that it includes the following steps: obtaining the target workflow and identifying each task in the target workflow; obtaining the credibility of each service provider in executing the task, and obtaining the time cost of each service provider in executing each task in the target workflow, the time cost including the task transmission time cost and the task execution time cost; matching the target service provider of each task according to the time cost and credibility of each service provider, so that the total execution time cost of the target workflow in a trusted environment is the lowest. The present invention ensures the rationality and efficiency of task allocation by comprehensively considering the execution efficiency and reliability of the service provider, which can not only improve the resource utilization and task execution speed in the cloud computing environment, but also reduce the risk of task failure caused by unreliable service providers, which helps to provide a more reliable and efficient solution for the business operation of enterprises or organizations on the cloud computing platform.

[0006] Optionally, the credibility of any service provider in executing a task is obtained through the following steps: obtaining the execution results of the service provider on historical tasks, the execution results being completed or incomplete; predicting the completion probability of the service provider for the task to be executed based on the execution results of the service provider on historical tasks, the task to be executed being a task in the target workflow; obtaining the user's feedback evaluation on the execution results, the feedback evaluation being the execution result satisfaction score; obtaining the credibility of the service provider in executing the task to be executed based on the completion probability of the task to be executed by the service provider and the average feedback score. The present invention ensures that each task can select a credible service provider when it is assigned, thereby reducing the risk of task failure and improving the execution efficiency and reliability of the overall workflow, and can provide a guaranteed solution for task scheduling in a cloud computing environment.

[0007] Optionally, the completion probability of a service provider for a task to be executed satisfies the prediction model. The completion probability prediction model of a service provider for a task to be executed provided by the present invention can accurately evaluate the performance of the service provider in future tasks, thereby optimizing the task allocation strategy and ensuring that tasks are allocated to service providers with high completion probability.

[0008] Optionally, the average feedback score of any service provider satisfies the calculation model. The present invention introduces user feedback evaluation, incorporates user experience and service quality into scheduling decisions to optimize task allocation, and helps provide a more reliable and user-satisfying solution for task scheduling in a cloud computing environment.

[0009] Optionally, the credibility of any service provider for executing the task satisfies the calculation model. The present invention not only improves the success rate of task execution, but also enhances the stability of service quality and user satisfaction by comprehensively considering the completion probability of the service provider and user feedback, and provides a more scientific and comprehensive solution for task scheduling in a cloud computing environment, thereby improving the efficiency and reliability of the overall workflow.

[0010] Optionally, the target service provider of each task is matched according to the time cost and credibility of each service provider, so that the total execution time cost of the target workflow in the trusted environment is minimized, including the following steps: generating credibility constraints according to the credibility requirements of the execution environment of each task; obtaining the optional service providers of each task according to the credibility constraints of each task; matching the target service provider from the optional service providers of each task respectively, so that the total execution time cost of the target workflow is minimized. The present invention ensures that when selecting a service provider, not only the time cost is considered, but also the credibility constraints are strictly followed, so as to ensure that the task is carried out in a trusted environment while ensuring efficient execution of the task.

[0011] Optionally, the target service provider of each task is matched according to the time cost and credibility of each service provider, so that the total execution time cost of the target workflow in a trusted environment is minimized, and the following steps are also included: identifying the dependency relationship between each task in the target workflow and other tasks, and marking the execution order of each task in the target workflow according to the dependency relationship. The present invention clarifies the dependency relationship of each task to reasonably arrange the execution order of the tasks, thereby avoiding execution confusion and inefficiency caused by improper handling of task dependencies, thereby improving the overall execution efficiency of the workflow.

[0012] Optionally, matching the target service provider from the optional service providers of each task respectively so that the total execution time cost of the target workflow is minimized includes the following steps: obtaining the first optional service provider for the first execution task, and selecting the service provider with the lowest first total cost as the first target service provider from the first optional service providers, wherein the first total cost is the time cost of the first optional service provider to perform the first execution task; obtaining the second optional service provider for the second execution task, and respectively obtaining the data transmission time cost between the first target service provider and each second optional service provider, and selecting the service provider with the lowest second total cost from the second optional service providers as the second target service provider, wherein the second total cost is the sum of the time cost of the second optional service provider to perform the second execution task and the data transmission time cost between the first target service provider and the second optional service provider; based on the selection method of the second target service provider, gradually selecting the third target service provider for the third execution task, the fourth target service provider for the fourth execution task, and so on, until the Nth target service provider for the Nth execution task is selected. The present invention ensures the comprehensive minimum of the execution time cost and data transmission time cost of each task through gradual optimization, which not only helps to improve the utilization efficiency of cloud resources, but also helps to provide an efficient and economical solution for cloud computing task scheduling in a cloud computing environment.

[0013] In a second aspect, the computer-readable storage medium provided by the present invention stores a computer program, and when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the cloud computing workflow scheduling method based on time cost and credibility constraints provided in the first aspect. The present invention enables the cloud computing work scheduling method to be automatically run on a computer device, ensuring the efficiency, reliability and repeatability of the method implementation process, and can provide a convenient and effective cloud computing scheduling tool for enterprises or organizations.

[0014] In a third aspect, the computer program product provided by the present invention includes computer instructions, which are stored in a computer-readable storage medium, and are suitable for being read and executed by a processor, so that a computer device having the processor executes the cloud computing workflow scheduling method based on time cost and credibility constraints provided in the first aspect. The present invention can provide an enterprise or organization with a fully automated and intelligent scheduling solution in a cloud computing environment, which can not only ensure the efficient management and execution of business processes, but also improve the utilization rate of cloud computing resources and the reliability of task execution. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The flowchart of the cloud computing workflow scheduling method based on time cost and credibility constraints is shown;

[0016] Figure 2 A schematic diagram of a target workflow provided in an embodiment of the present invention;

[0017] Figure 3 A flowchart of credibility assessment of a task performed by a service provider provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0019] In one embodiment, see Figure 1 , Figure 1 The flowchart of the cloud computing workflow scheduling method based on time cost and credibility constraints provided by the embodiment of the present invention is as follows. Figure 1 As shown, the cloud computing workflow scheduling method based on time cost and credibility constraints provided by the embodiment of the present invention includes the following steps:

[0020] S01. Acquire a target workflow, and identify each task in the target workflow.

[0021] In this embodiment, the target workflow refers to a set of related tasks that need to be executed in a cloud computing environment in a specific order and with dependencies to complete a specific business process.

[0022] Furthermore, each task in the target workflow represents an independent calculation or processing step; each task can be independently executed by different cloud service providers, and there are dependencies between the tasks.

[0023] See also Figure 2 , Figure 2 FIG. 1 is a schematic diagram of a target workflow provided in an embodiment of the present invention. Figure 2 As shown, the target workflow Q includes multiple tasks from q1 to q7, each of which can be independently executed by a service provider, but the execution order of each task is limited by its dependency on other tasks.

[0024] S02. Obtain the credibility of each service provider in executing tasks, and obtain the time cost of each service provider in executing each task in the target workflow.

[0025] In this embodiment, the credibility refers to the reliability and stability of the service provider in executing tasks in the cloud computing environment. Specifically, the credibility evaluation is based on the service provider's completion of historical tasks and user feedback evaluation, which is specifically reflected in the success probability and user satisfaction of the service provider in future task execution.

[0026] For further information, see Figure 3 , Figure 3 This is a flow chart of the credibility assessment of a service provider performing a task provided by an embodiment of the present invention. Figure 3 As shown in the figure, the credibility of any service provider in performing tasks can be obtained through the following steps:

[0027] S021. Obtain the execution results of the service provider for the historical tasks.

[0028] In this embodiment, the execution result is completed or not completed; in other embodiments, the execution result can also be represented by the percentage of task completion.

[0029] Furthermore, the execution result can be obtained by analyzing the task logs provided by the service provider, monitoring system records, and collecting relevant data in the task management system.

[0030] S022. Predict the completion probability of the task to be executed by the service provider based on the execution results of the historical tasks by the service provider.

[0031] In this embodiment, the execution capability and stability of the service provider are understood by analyzing the historical task execution results, and the completion probability of the task to be executed is predicted. It can be understood that the task to be executed is any task in the target workflow.

[0032] Furthermore, the completion probability of any service provider for the task to be executed satisfies the following prediction model: Among them, e i represents the completion probability of the i-th service provider, p th represents the completion probability threshold, S represents the number of historical tasks whose execution results are completed, F represents the number of historical tasks whose execution results are uncompleted, p represents the completion probability, and ! represents the factorial symbol.

[0033] S023. Obtain the user's feedback and evaluation on the execution result, where the feedback and evaluation is the execution result satisfaction score.

[0034] In this embodiment, the execution result satisfaction score refers to the feedback score given by the user to the cloud service provider after executing the task, which is used to evaluate the performance and service quality of the service provider in completing the task.

[0035] Furthermore, the execution result satisfaction score is usually collected through questionnaires, evaluation systems or feedback platforms, reflecting the user's satisfaction in a quantitative form; it can be understood that the higher the execution result satisfaction score is, the more satisfied the user is with the task execution result.

[0036] S024. Obtain the credibility of the service provider in executing the task to be executed based on the completion probability of the task to be executed by the service provider and the average feedback score.

[0037] In this embodiment, the average feedback score refers to the average of the satisfaction scores of different users on the service provider's execution of different user tasks, which reflects the service quality of the service provider.

[0038] Furthermore, the average feedback score of any service provider satisfies the following calculation model: Among them, i represents the average feedback score of the ith service provider, M represents the total number of samples of satisfaction scores of the execution results, and Score represents the satisfaction scores of the execution results. It can be understood that the samples of satisfaction scores of the execution results can be the satisfaction scores of the execution results of a user for multiple execution tasks, or the satisfaction scores of the execution results of multiple users for multiple execution tasks.

[0039] Furthermore, based on the completion probability and average feedback score of the service provider for the task being executed, the credibility of any service provider for the task being executed satisfies the following calculation model: C i =k e ·e i +k o |o i , where C i,j represents the credibility of the i-th service provider, k e +k o =1, k e represents the completion probability credibility influence weight, e i represents the completion probability of the i-th service provider, k o represents the impact weight of the credibility of feedback evaluation, o i Represents the average feedback score of the i-th service provider.

[0040] In this embodiment, the time cost of any task includes the task transmission time cost and the task execution time cost. Further, the task transmission time cost refers to the transmission time of a task from cloud storage or local device to the target service provider; the task execution time cost refers to the time it takes for the target service provider to execute a task, specifically including the total time required to process data, calculate and generate output results.

[0041] S03. Match the target service provider for each task according to the time cost and credibility of each service provider, so that the total execution time cost of the target workflow in the trusted environment is minimized.

[0042] In this embodiment, by comprehensively considering the time cost and credibility of each service provider, the optimal service provider is selected for each task in the target workflow to ensure that each task is executed in a trusted environment and minimize the total execution time cost of the entire target workflow.

[0043] Furthermore, the step S03 provides matching the target service provider of each task according to the time cost and credibility of each service provider, so that the total execution time cost of the target workflow in the trusted environment is minimized, including the following steps:

[0044] S031. Generate credibility constraints according to the credibility requirements of the execution environment of each task.

[0045] It can be understood that the credibility constraint refers to the minimum requirement for the reliability and stability of the service provider during the task allocation process; specifically, in this embodiment, the credibility constraint of each task refers to the minimum credibility of the service provider performing the task.

[0046] Furthermore, each task may have different execution environment trustworthiness requirements, depending on the importance of the task, data sensitivity, and business requirements. For example, business-critical tasks may require higher trustworthiness, while secondary tasks may allow for lower trustworthiness.

[0047] S032. Obtain optional service providers for each task based on the credibility constraints of each task.

[0048] Furthermore, through the credibility constraint set in step S031, a credibility threshold is set for each task, and only service providers that reach or exceed this threshold can be considered as optional service providers for the task. For example, the credibility threshold of task q1 is set to 0.85, which means that only service providers with a credibility greater than or equal to 0.85 can perform the task.

[0049] S033. Match the target service provider from the optional service providers of each task respectively, so that the total execution time cost of the target workflow is minimized.

[0050] Furthermore, in order to optimize the total execution time cost of the target workflow based on the trusted environment, step S03 further includes the following steps:

[0051] S034: Identify the dependency relationship between each task in the target workflow and other tasks, and mark the execution order of each task in the target workflow according to the dependency relationship.

[0052] In this embodiment, the dependency relationship refers to the mutual dependency between tasks, that is, a task can only be executed after another task is completed.

[0053] It can be understood that dependencies determine the execution order of tasks, ensuring that tasks are processed in a logical order to ensure data correctness and business process consistency. Furthermore, the execution order of tasks is marked based on dependencies to ensure that each task is executed only after all its predecessor tasks are completed.

[0054] like Figure 2 As shown, task q1 has no dependencies and is executed first; task q2 depends on task q1 and is executed after task q1 is completed; task q3 depends on task q2 and is executed after task q2 is completed; task q4 depends on task q2 and is executed after task q2 is completed; task q5 depends on task q3 and task q4 and is executed after task q3 and task q4 are completed; task q6 depends on task q3 and task q5 and is executed after task q3 and task q5 are completed; task q7 depends on task q6 and task q4 and is executed after task q6 and task q4 are completed.

[0055] Further, based on the above dependency relationship, task q1 is set as the first execution task; task q2 is set as the second execution task; tasks q3 and q4 are set as the third execution task; task q5 is set as the fourth execution task; task q6 is set as the fifth execution task; and task q7 is set as the sixth execution task.

[0056] Further, based on the task execution order marked in step S034, the step S033 matches the target service provider from the optional service providers of each task respectively, so that the total execution time cost of the target workflow is minimized, specifically including the following steps:

[0057] A first optional service provider for the first execution task is obtained, and a service provider with the lowest first total cost and time cost is selected from the first optional service providers as the first target service provider, where the first total cost is the time cost of the first optional service provider to execute the first execution task.

[0058] Obtain the second optional service provider for the second execution task, and respectively obtain the data transmission time cost between the first target service provider and each second optional service provider, and select the service provider with the lowest second total cost among the second optional service providers as the second target service provider, where the second total cost is the sum of the time cost of the second optional service provider performing the second execution task and the data transmission time cost between the first target service provider and the second optional service provider.

[0059] Based on the selection method of the second target service provider, the third target service provider for the third execution task, the fourth target service provider for the fourth execution task, ... are gradually selected until the Nth target service provider for the Nth execution task is selected.

[0060] It should be noted that in the process of selecting the target service provider for any type of execution task from the second execution task to the Nth execution task, if two or more target service providers of the same type of execution tasks are the same, then the target service providers of the same type of execution tasks will be further selected one by one from low to high according to the total time cost, so that when executing the same type of tasks, one target service provider corresponds to only one execution task, thereby avoiding target server conflicts and execution bottlenecks.

[0061] In one embodiment, the present invention further provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program, and when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned cloud computing workflow scheduling method based on time cost and credibility constraints. For technical details not disclosed in the computer-readable storage medium embodiment involved in this embodiment, please refer to the description of the above-mentioned method embodiment. In addition, the description of the beneficial effects of using the same method will not be repeated.

[0062] Furthermore, the computer program may be deployed to be executed on one computing device, or on multiple computing devices located at one location, or on multiple computing devices distributed at multiple locations and interconnected by a communication network. Multiple computing devices distributed at multiple locations and interconnected by a communication network may constitute a corresponding cloud computing system.

[0063] In one embodiment, the present invention further provides a computer program product, which includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device can execute the above-mentioned cloud computing workflow scheduling method based on time cost and credibility constraints. The specific method implementation details are not repeated here. In addition, the description of the beneficial effects of using the same method is not repeated.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents.

Claims

1. A cloud computing workflow scheduling method based on time cost and credibility constraints, characterized in that: The steps include: Acquire a target workflow and identify each task in the target workflow; Obtaining the credibility of each service provider in executing tasks, and obtaining the time cost of each service provider in executing each task in the target workflow, wherein the time cost includes the task transmission time cost and the task execution time cost; According to the time cost and credibility of each service provider, the target service provider of each task is matched so that the total execution time cost of the target workflow in the trusted environment is minimized.

2. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 1 is characterized in that: The credibility of any service provider in performing tasks can be obtained through the following steps: Obtain the execution result of the service provider for the historical task, where the execution result is completed or not completed; Predicting the completion probability of a task to be executed by the service provider based on the execution results of historical tasks by the service provider, where the task to be executed is a task in the target workflow; Obtaining user feedback on the execution result, wherein the feedback is a satisfaction score of the execution result; The credibility of the service provider in executing the task to be executed is obtained based on the completion probability of the task to be executed by the service provider and the average feedback score.

3. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 2 is characterized in that: The completion probability of a task to be executed by a service provider satisfies the prediction model.

4. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 3 is characterized in that: The average feedback score of a service provider that satisfies the calculation model.

5. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 4 is characterized in that: The trustworthiness of a service provider in executing tasks satisfies the calculation model.

6. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 1, characterized in that: The method of matching the target service provider of each task according to the time cost and credibility of each service provider so that the total execution time cost of the target workflow in the trusted environment is minimized includes the following steps: Generate trust constraints based on the trustworthiness requirements of the execution environment of each task; Obtain the optional service providers for each task according to the credibility constraints of each task; The target service provider is matched from the optional service providers of each task respectively so that the total execution time cost of the target workflow is minimized.

7. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 6 is characterized in that: The step of matching the target service provider of each task according to the time cost and credibility of each service provider so that the total execution time cost of the target workflow in the trusted environment is minimized also includes the following steps: Identify the dependency relationship between each task in the target workflow and other tasks, and mark the execution order of each task in the target workflow according to the dependency relationship.

8. The cloud computing workflow scheduling method based on time cost and credibility constraints according to claim 7 is characterized in that: The step of matching the target service provider from the optional service providers of each task respectively so that the total execution time cost of the target workflow is minimized comprises the following steps: Obtain a first optional service provider for the first execution task, and select a service provider with the lowest first total cost and time cost from the first optional service providers as a first target service provider, where the first total cost is the time cost of the first optional service provider for executing the first execution task; Obtain a second optional service provider for the second execution task, and respectively obtain the data transmission time cost between the first target service provider and each second optional service provider, and select the service provider with the lowest second total cost among the second optional service providers as the second target service provider, where the second total cost is the sum of the time cost of the second optional service provider performing the second execution task and the data transmission time cost between the first target service provider and the second optional service provider; Based on the selection method of the second target service provider, the third target service provider for the third execution task, the fourth target service provider for the fourth execution task, ... are gradually selected until the Nth target service provider for the Nth execution task is selected.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the cloud computing workflow scheduling method based on time cost and credibility constraints according to any one of claims 1 to 8.

10. A computer program product, characterized in that The computer program product includes computer instructions, which are stored in a computer-readable storage medium, and the computer instructions are suitable for being read and executed by a processor, so that a computer device having the processor executes the cloud computing workflow scheduling method based on time cost and credibility constraints as described in any one of claims 1-8.

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