Niching Particle Swarm Optimization Algorithm for Solving Task Scheduling in Cloud Computing

被引：0

作者：

Gan Na ^{[1
]}

Huang Yufeng ^{[1
]}

Lu Xiaomei ^{[1
]}

机构：

[1] Guangdong Engn Polytech, Informat Engn Dept, Guang Zhou 510520, Guangdong, Peoples R China

来源：

AGRO FOOD INDUSTRY HI-TECH | 2017年 / 28卷 / 03期

关键词：

cloud task Scheduling; the niche technology; Shrinkage factor; the parallel thread;

D O I：

暂无

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

According to the characteristics of task scheduling in cloud computing, a niche particle swarm optimization algorithm is proposed to solve cloud task scheduling problem. Based on the standard particle swarm algorithm, this paper introduces the niche technology, introduces the parallel thread, accelerates the optimization speed, and can balance the global and local search ability. The velocity and the updating equation of the particle are added with the shrinkage factor. Finally, a method for solving cloud task scheduling is given. Through the simulation of cloud task scheduling system, the experimental results show that this algorithm not only overcomes the shortcomings of PSO algorithm in local optimization, but also improves the convergence precision. It has a good effect in shortening the execution time, cost and load balance, and is an effective cloud task scheduling algorithm.

引用

页码：876 / 879

页数：4

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