JOURNAL ARTICLE

Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm

Jianwen LiChiwen Qu

Year: 2016 Journal:   MATEC Web of Conferences Vol: 40 Pages: 09008-09008   Publisher: EDP Sciences

Abstract

\nThe task scheduling strategy based on cultural genetic algorithm(CGA) is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.\n

Keywords:
Computer science Cloud computing Distributed computing Scheduling (production processes) Fair-share scheduling Cultural algorithm Mathematical optimization Dynamic priority scheduling Genetic algorithm Population-based incremental learning Mathematics Machine learning Quality of service Computer network Operating system

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
8
Refs
0.04
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced Technology in Applications
Physical Sciences →  Computer Science →  Information Systems

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