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Cloud task scheduling method based on improved genetic algorithm

An improved genetic algorithm and task scheduling technology, applied in the field of cloud task scheduling based on the improved genetic algorithm, can solve the problems of short total time and average time, lack of consideration of the average execution time of tasks, etc., and achieve the goal of improving parallelism and avoiding blocking problems Effect

Active Publication Date: 2014-07-02
ZHUHAI XIANG YI AVIATION TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of lack of consideration of the average execution time of tasks in the current scheduling algorithm, and find out the sequence of resource nodes for executing tasks in the Map / Reduce programming model.

Method used

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  • Cloud task scheduling method based on improved genetic algorithm
  • Cloud task scheduling method based on improved genetic algorithm
  • Cloud task scheduling method based on improved genetic algorithm

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Embodiment Construction

[0029] The method of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0030] Such as figure 1 , the specific implementation steps of the method of the present invention are as follows:

[0031] Step 1: Encoding and Decoding

[0032] The individual chromosome is encoded, the length of the chromosome is the sum of the number of subtasks, and the value of each gene in the chromosome is the resource number assigned to the resource by the subtask.

[0033] Assuming there are T tasks, each task can be divided into multiple subtasks, the number of subtasks divided into subtasks for the i-th task is subNum, and the total number of subtasks is subTotal:

[0034] subTotal = Σ i = 0 T - 1 subNum - - -...

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Abstract

The invention provides a cloud task scheduling method based on an improved genetic algorithm which is the dual fitness multiplied genetic algorithm, and relates to the fields of cloud computing and scheduling algorithms. As for a cloud computing Map / Reduce programming model, the problem of matching between user tasks and virtual resources is researched to find appropriate resources for execution of the user tasks, the total task execution time and the mean task execution time are shortest at the same time through the algorithm, and according to the algorithm, one fitness and one multiplied algorithm comprehensively adopting task scheduling are added. An initial population is generated, the individual fitness value is calculated, the operations of selection, intersection and mutation are carried out, the number of iteration is added by one, new populations are generated constantly, the individual fitness values of the finally-obtained population are calculated respectively, the individual with the largest fitness value is the optimal solution, and a resource node sequence obtained by decoding the individual is the final result of the cloud task scheduling method based on the improved genetic algorithm.

Description

technical field [0001] The invention relates to two fields of cloud computing and scheduling algorithms, in particular to a cloud task scheduling method based on an improved genetic algorithm. Background technique [0002] The advent of the intelligent information age has led to the birth of a new computing model - cloud computing. Compared with the previous grid computing, cloud computing has the characteristics of ultra-large scale, virtualization, scalability, on-demand service, and manageability, so it has attracted the attention and favor of major manufacturers and researchers. Cloud computing mainly uses virtualization technology to virtualize various resources, including computing resources, network resources, and storage resources, into resource pools for unified management and external services. It is obvious that the user groups of cloud computing are very extensive, and the amount of tasks and data to be processed is also very large. The system is processing mass...

Claims

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Application Information

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IPC IPC(8): G06F9/48G06F9/50G06N3/12H04L29/08
Inventor 王冠梁社静周珺陈建中张少华
Owner ZHUHAI XIANG YI AVIATION TECH CO LTD
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