Volume 9 Number 4 (Apr. 2014)
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JSW 2014 Vol.9(4): 895-901 ISSN: 1796-217X
doi: 10.4304/jsw.9.4.895-901

Resource Scheduling Optimization Algorithm of Energy Consumption for Cloud Computing Based on Task Tolerance

Liang Hao, Gang Cui, Mingcheng Qu, Wende Ke
Department of Computer Science and Technology, Harbin Institution of Technology, Harbin, China

Abstract—In order to solve that the energy was seriously wasted in cloud computing, an algorithm of energy consumption optimization for cloud computing based on the task tolerance (ECCT) was proposed. The concept of the task tolerance was put forward in the algorithm. The resource utilization of cloud computing node was maximized through increasing the task tolerance. At the same time, the parallelism degree of tasks were increased so that the task waiting time was reduced, which led to a reduction of energy consumption in cloud computing. Parameters were estimated and experiments on actual cloud computing sets were illustrated. The results showed that the total energy consumption and executive time were reduced more in the proposed algorithm than sequential executive algorithm (SEA). In addition, the advantage would be increasingly apparent with the increasing in assignments.1

Index Terms—cloud computing, task tolerance, resource utilization, energy consumption optimization

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Cite: Liang Hao, Gang Cui, Mingcheng Qu, Wende Ke, "Resource Scheduling Optimization Algorithm of Energy Consumption for Cloud Computing Based on Task Tolerance," Journal of Software vol. 9, no. 4, pp. 895-901, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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