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A resource allocation and task scheduling multi-target cooperative processing method

A task scheduling and resource allocation technology, applied in the information field, can solve problems such as the inability to achieve resource allocation benefits, the inability to take into account the dynamics and maximization of task scheduling, etc.

Inactive Publication Date: 2019-05-31
SHENZHEN INST OF ADVANCED TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Existing research work cannot maximize resource allocation benefits when scheduling tasks
The dynamics of task scheduling cannot be considered in resource optimization, and there is a lack of a general framework model that can monitor and track application execution and changes in real time, and coordinate task scheduling and resource allocation.

Method used

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  • A resource allocation and task scheduling multi-target cooperative processing method
  • A resource allocation and task scheduling multi-target cooperative processing method
  • A resource allocation and task scheduling multi-target cooperative processing method

Examples

Experimental program
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Effect test

Embodiment

[0035]

[0036] Table 1: A set of production rules for computational offloading

[0037] Such as figure 2 : This example uses the rules in Table 1 to implement a dynamic "allocation-scheduling-unloading" process. First, according to the unloading rules, the sub-objective "task scheduling" is pushed into the target stack, and then the "task graph" (indicating that the task graph model has been generated) and "performance" (indicating that the performance needs to be optimized) describing the scene is placed in the descriptive knowledge module. Due to the addition of new goals and new knowledge blocks, the preconditions for calculating the segmentation rules have been met, and the rules are then stimulated to execute, and the new sub-goal "resource allocation" is pushed into the goal stack. Resource allocation rules are stimulated and executed to achieve resource optimization. The optimized application and resource characteristics ("CPU utilization is greater than 60%, net...

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Abstract

The invention relates to the technical field of information. The resource allocation and task scheduling multi-target cooperative processing method comprises the following steps: S1, , storing long-term invariant situational knowledge accumulated by a system through an environmental knowledge module, extracting environmental characteristics and application characteristics by using a machine learning method, and forming a knowledge block in a tuple form for storage by using the environmental characteristics and the application characteristics as descriptive knowledge; S2, using a task scheduling module and a resource distribution module to store procedural knowledge in the form of conditions-actions. In the calculation process, knowledge blocks in a calculation environment module are matched with all productive expressions in the task scheduling module and a resource distribution module, and if the premise condition of a certain productive expression is met, a productive expression ruleis triggered and updated. According to the invention, system continuous scene monitoring cognition and resource allocation and task scheduling cooperative operation can be realized, and the purpose of side cloud cooperative self-adaption is achieved.

Description

technical field [0001] The present invention relates to the field of information technology, in particular to a multi-objective collaborative processing method for resource allocation and task scheduling. Background technique [0002] Edge computing and cloud computing are complementary. Edge-cloud collaboration is the product of the combination of edge computing and cloud computing. The organic combination of the two will greatly improve the information processing efficiency of edge computing in the era of Internet of Everything. In the edge-cloud collaborative environment, how to schedule computing resources is one of the important challenges. Task scheduling in an edge-cloud collaborative environment is related to resource allocation. The task scheduling strategy can guarantee the resources used by an application in the system during execution. The task scheduling strategy maximizes the use of limited computing resources to improve the executable program in the edge comp...

Claims

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Application Information

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IPC IPC(8): G06F9/50G06F9/48
Inventor 王洋吕静雅赵娟娟须成忠
Owner SHENZHEN INST OF ADVANCED TECH
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