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A multi-objective krill herd algorithm for virtual machine placement in cloud computing

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Abstract

In cloud computing, the major task is to make efficient use of resources. The growth in cloud environment opens door for vast research. Placement of virtual machine is a main problem in cloud environment. The ideal placement of virtual machine leads to power effectiveness and asset usage in distributed cloud computing. A multi-objective krill herd technique is proposed in this paper for placement of virtual machine. The objective is to effectively acquire an arrangement of non-dominated solutions that the entire limit add up to asset wastage and power utilization. The work is analysed with the examples from the literature. The experimental outcomes are compared with the existing multi-objective genetic procedure and multi-objective ant colony algorithm. Also, the results are compared with the 2 algorithms, First Fit Decreasing algorithm and Simplified Ant Colony algorithm. The experimental results shows that the proposed method is more efficient when compared to other existing methods.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Annamalai University, Chidambaram, India

    K. M. Baalamurugan & S. Vijay Bhanu

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  1. K. M. Baalamurugan
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  2. S. Vijay Bhanu
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Correspondence to K. M. Baalamurugan.

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Baalamurugan, K.M., Vijay Bhanu, S. A multi-objective krill herd algorithm for virtual machine placement in cloud computing. J Supercomput 76, 4525–4542 (2020). https://doi.org/10.1007/s11227-018-2516-1

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