Heuristic Task Consolidation Techniques for Energy Efficient Cloud Computing

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Author(s): Dilip Kumar (National Institute of Technology, India), Bibhudatta Sahoo (National Institute of Technology, India)and Tarni Mandal (National Institute of Technology, India)
Copyright: 2016
Pages: 23
Source title: Web-Based Services: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-9466-8.ch034

Keywords: Computer Science & IT / Information Science Reference / Web Technologies / Web Technologies & Engineering

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Abstract

The energy consumption in the cloud is proportional to the resource utilization and data centers are almost the world's highest consumers of electricity. The complexity of the resource allocation problem increases with the size of cloud infrastructure and becomes difficult to solve effectively. The exponential solution space for the resource allocation problem can be searched using heuristic techniques to obtain a sub-optimal solution at the acceptable time. This chapter presents the resource allocation problem in cloud computing as a linear programming problem, with the objective to minimize energy consumed in computation. This resource allocation problem has been treated using heuristic approaches. In particular, we have used two phase selection algorithm ‘FcfsRand', ‘FcfsRr', ‘FcfsMin', ‘FcfsMax', ‘MinMin', ‘MedianMin', ‘MaxMin', ‘MinMax', ‘MedianMax', and ‘MaxMax'. The simulation results indicate in the favor of MaxMax.

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Heuristic Task Consolidation Techniques for Energy Efficient Cloud Computing

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