Improved FIFO scheduling algorithm based on fuzzy clustering in cloud computing

被引：15

作者：

Li J. ^{[1
]}

Ma T. ^{[1
]}

Tang M. ^{[1
]}

Shen W. ^{[3
]}

Jin Y. ^{[4
]}

机构：

[1] School of Computer Software, Nanjing University of Information Science and Technology, Nanjing

[2] CICAEET, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing

[3] National Meteorological Information Center, Beijing

[4] Department of Mathematics, YanBian University, Yanji

来源：

Ma, Tinghuai (thma@nuist.edu.cn) | 1600年 / MDPI AG卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Cloud computing; FIFO; Fuzzy clustering algorithms; Resource clustering; Scheduling algorithm;

D O I：

10.3390/info8010025

中图分类号：

学科分类号：

摘要：

In cloud computing, some large tasks may occupy too many resources and some small tasks may wait for a long time based on First-In-First-Out (FIFO) scheduling algorithm. To reduce tasks' waiting time, we propose a task scheduling algorithm based on fuzzy clustering algorithms. We construct a task model, resource model, and analyze tasks' preference, then classify resources with fuzzy clustering algorithms. Based on the parameters of cloud tasks, the algorithm will calculate resource expectation and assign tasks to different resource clusters, so the complexity of resource selection will be decreased. As a result, the algorithm will reduce tasks' waiting time and improve the resource utilization. The experiment results show that the proposed algorithm shortens the execution time of tasks and increases the resource utilization.

引用

共 18 条

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