An effective task scheduling algorithm based on dynamic energy management and efficient resource utilization in green cloud computing environment
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With the expanding of its scale and the energy cost factors being ignored in green cloud computing, the problem of high energy cost and low efficiency is exposed. Based on the concepts and principles of load balancing, a novel energy-efficient load balancing global optimization algorithm, called resource-aware load balancing clonal algorithm for task scheduling, is proposed to deal with the problem of energy consumption in green cloud computing. Firstly, the problem is formulated as a combinatorial optimization problem that aims to optimize both energy consumption and load balancing. Then, the resource-aware scheduling algorithm is proposed based on load balancing strategy and clonal selection principle. Finally, simulation studies show that the proposed algorithm can effectively reduce energy consumption in green cloud computing, and its exploration and exploitation abilities can be enhanced and well balanced.
KeywordsGreen cloud computing Energy consumption constraint Data centers Combinatorial optimization problem Clonal selection resource scheduling algorithm
This work is supported by the project of the First-Class University and the First-Class Discipline(10301-017004011501), and the National Natural Science Foundation of China.
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