Quadratic Particle Swarm Optimisation Algorithm for Task Scheduling Based on Cloud Computing Server

被引:2
|
作者
Wei, Guanghui [1 ]
机构
[1] Chongqing Coll Elect Engn, Artificial Intelligence & Big Data Coll, Chongqing 401331, Peoples R China
关键词
Cloud computing; particle swarm optimisation (PSO); quadratic particle swarm optimisation (QPSO);
D O I
10.1142/S0219649222500678
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
The task scheduling is one of the core problems of cloud computing and aims to assign tasks reasonably, realise the optimal scheduling strategy and improve the operating efficiency of overall cloud computing system. For the shortcomings of traditional particle swarm optimisation (PSO) algorithm in total completion time and average completion time, a quadratic particle swarm optimisation (QPSO) algorithm is proposed. Using the proposed algorithm, people can find a scheduling result with the short total completion time of task and also ensuring the short average completion time of task. Finally, the research made a simulation experiment with Cloud Sim. Experiment results show that in the same condition setting, the algorithm proposed is superior to the traditional PSO algorithm. When the number of tasks increases, the comprehensive scheduling performance of QPSO is more than 20% higher than that of PSO.
引用
收藏
页数:13
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