Method and system for task analysis and resource allocation based on formal model

A technology for resource allocation and tasks, applied in the field of computer science, can solve the problems of low task completion rate of edge nodes, real-time requirements of the Internet of Everything, task failure, etc., and achieve the effect of good scalability

CN113010296BActive Publication Date: 2022-07-26SHANGHAI JIAOTONG UNIV
0 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2022-07-26

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The present invention provides a method and system for task analysis and resource allocation based on a formal model, including: step S1: a task analysis module analyzes task requirements, and formally expresses the task requirements as a task workflow; step S2: a resource allocation module Combine the formalized task workflows to obtain a combined task workflow; step S3: abstract the resource capabilities of the mobile terminal device into a meta model, and perform service registration in the cloud; step S4: based on the combined task workflow and For the service registered in the cloud, a heuristic algorithm is used to perform task scheduling and matching; step S5 : the mobile terminal device executes the task according to the scheduling matching result.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The present invention relates to the field of computer science, in particular, to a method and system for task analysis and resource allocation based on a formal model, and more particularly, to a method and system for task analysis and resource allocation based on a formal model oriented to mobile edge computing scenarios. system. Background technique

[0002] As edge computing continues to develop, it can circumvent the long distances, capacity constraints, multiple network hops, and centralized handling of loads in traditional Internet architectures. At present, the number of devices connected to the Internet has become very large, and the amount of data is also increasing every day. The traditional cloud computing model is to upload all data to the cloud computing center through the network, and use the super computing power of cloud computing to solve the calculation of centralized applications. However, it has three shortcomings: 1. The real-tim...

Examples

Embodiment 1

[0051] A method for task analysis and resource allocation based on a formal model provided according to the present invention, comprising:

[0052] Step S1: the task analysis module analyzes the task requirements, and formally expresses the task requirements as a task workflow;

[0053] Step S2: the resource allocation module merges the formalized task workflows based on the total resources consumed by the reduced workflows to obtain a combined task workflow;

[0054] Step S3: abstracting the resource capabilities of the mobile terminal device into a meta model, and performing service registration in the cloud;

[0055] Step S4: Based on the combined task workflow and the service registered in the cloud, a heuristic algorithm is used to perform task scheduling and matching;

[0056] Step S5: The mobile terminal device executes the task according to the scheduling matching result.

[0057] Specifically, the step S1 includes:

[0058] Step S1.1: using the method of combining ...

Embodiment 2

[0082] Embodiment 2 is a preferred example of Embodiment 1

[0083] In order to solve the task and resource management problems in mobile edge computing, the present invention proposes a formal model-based task analysis and resource allocation method for cross-domain resource cooperation. The method is mainly divided into three modules, a task analysis module, a resource allocation module and a mobile Internet of Things device module.

[0084] The task parsing module is used to abstract a batch of tasks into a resource requirement description meta-model, and the mobile IoT device module is used to abstract the device's ability to provide resources into a resource supply description meta-model and issue tasks. The resource allocation module is a combination of this. Two models are used to perform heuristics to generate task assignment plans for the final execution of tasks. This method can reduce the overhead of repetitive task parsing and find a relatively optimal task alloca...

Embodiment 3

[0096] Embodiment 3 is a preferred example of Embodiment 1 and / or Embodiment 2

[0097] The content of the present invention will be described in detail below in conjunction with specific implementation methods. Because the present invention mainly protects the task matching method based on mobile edge computing, and each module inside the system has various implementation methods, only one feasible strategy is given.

[0098] like Figure 1-5 As shown, the system architecture of the present invention is divided into three parts:

[0099] Task analysis module: used to analyze large-scale task requirements and formally represent task workflow;

[0100]Resource allocation module: used to merge formal workflows, and then match services with subtasks;

[0101] Mobile IoT device module: the carrier of task execution;

[0102] Specifically, the task parsing module includes the following: