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Information 2017, 8(1), 25; doi:10.3390/info8010025

Improved FIFO Scheduling Algorithm Based on Fuzzy Clustering in Cloud Computing

1
School of Computer Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
2
CICAEET, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing 210044, China
3
National Meteorological Information Center, Beijing 100080, China
4
Department of Mathematics, YanBian University, Yanji 133002, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 31 December 2016 / Revised: 16 February 2017 / Accepted: 17 February 2017 / Published: 24 February 2017
(This article belongs to the Section Information Systems)
View Full-Text   |   Download PDF [2679 KB, uploaded 24 February 2017]   |  

Abstract

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. View Full-Text
Keywords: cloud computing; fuzzy clustering algorithms; FIFO; scheduling algorithm; resource clustering cloud computing; fuzzy clustering algorithms; FIFO; scheduling algorithm; resource clustering
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Li, J.; Ma, T.; Tang, M.; Shen, W.; Jin, Y. Improved FIFO Scheduling Algorithm Based on Fuzzy Clustering in Cloud Computing. Information 2017, 8, 25.

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