An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

Chunling Cheng; Jun Li; Ying Wang

doi:10.1109/TST.2015.7040511

Tsinghua Science and Technology 2015, 20(1): 28-39 https://doi.org/10.1109/TST.2015.7040511

Open Access | Issue | Published: 12 February 2015

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

Show Author's Information Hide Author's Information Chunling Cheng(

), Jun Li, Ying Wang

College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 213001, China.

Keywords:

cloud computing, independent task scheduling, energy-saving, vacation queuing theory

Cite this article:

Cheng C, Li J, Wang Y. An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing. Tsinghua Science and Technology, 2015, 20(1): 28-39. https://doi.org/10.1109/TST.2015.7040511

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Abstract

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system. Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.

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About this article

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

Show Author's information Hide Author's Information Chunling Cheng(

), Jun Li, Ying Wang

College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 213001, China.

Abstract

Keywords: cloud computing, independent task scheduling, energy-saving, vacation queuing theory

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Acknowledgements

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Publication history

Received: 16 November 2014

Revised: 17 December 2014

Accepted: 06 January 2015

Published: 12 February 2015

Issue date: February 2015

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Acknowledgements

This work was supported by Research and Innovation Projects for Graduates of Jiangsu Graduates of Jiangsu Province (No. CXZZ12_0483) and the Science and Technology Support Program of Jiangsu Province (No. BE2012849).