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Cuckoo search based resource optimization of datacenters

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Abstract

With advancements in virtualization technology, datacenters are often faced with the challenge of managing large numbers of virtual machine (VM) requests. Due to this large amount of VM requests, it has become practically impossible to search all possible VM placements in order to find a solution that best optimizes certain design objectives. As a result, managers of datacenters have resorted to the employment of heuristic optimization algorithms for VM placement. In this paper, we employ the cuckoo search optimization (CSO) algorithm to solve the VM placement problem of datacenters. Firstly, we use the CSO to optimize the datacenter for the minimization of the number of physical machines used for placement. Secondly, we implement a multiobjective CSO algorithm to simultaneously optimize the power consumption and resource wastage of the datacenter. Simulation results show that both CSO algorithms outperform the reordered grouping genetic algorithm (RGGA), the grouping genetic algorithm (GGA), improved least-loaded (ILL) and improved FFD (IFFD) methods of VM placement.

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Notes

  1. NAS device is a dedicated server used for storing and sharing files.

  2. The terms “nests” and “egg” are used interchangeably to denote a VM placement solution

  3. This means the residual space within the server assuming that the particular VM is removed from the server

  4. In the server idle-state, the CPU is not used, thus power is consumed by other server peripherals other than the CPU

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Acknowledgements

The authors acknowledge King Fahd University of Petroleum & Minerals (KFUPM) for all support. The work was conducted as part of project COE-572132-2.

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Authors and Affiliations

  1. Center for Communications and IT Research, Research Institute, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Kingdom of Saudi Arabia

    Sadiq M. Sait

  2. Department of Computer Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Kingdom of Saudi Arabia

    Abubakar Bala & Aiman H. El-Maleh

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  1. Sadiq M. Sait
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  2. Abubakar Bala
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Correspondence to Sadiq M. Sait.

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Sait, S.M., Bala, A. & El-Maleh, A.H. Cuckoo search based resource optimization of datacenters. Appl Intell 44, 489–506 (2016). https://doi.org/10.1007/s10489-015-0710-x

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