Energy-efficient Virtual Machine Allocation Technique Using Flower Pollination Algorithm in Cloud Datacenter: A Panacea to Green Computing

Usman, Mohammed Joda, Ismail, Abdul Samad, Chizari, Hassan ORCID: 0000-0002-6253-1822, Abdul-Salaam, Gaddafi, Usman, Ali Muhammad, Gital, Abdulsalam Yau, Kaiwartya, Omprakash and Aliyu, Ahmed (2019) Energy-efficient Virtual Machine Allocation Technique Using Flower Pollination Algorithm in Cloud Datacenter: A Panacea to Green Computing. Journal of Bionic Engineering, 16 (2). pp. 354-366. ISSN 1672-6529

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Abstract

Cloud computing has attracted significant interest due to the increasing service demands from organizations offloading computationally intensive tasks to datacenters. Meanwhile, datacenter infrastructure comprises hardware resources that consume high amount of energy and give out carbon emissions at hazardous levels. In cloud datacenter, Virtual Machines (VMs) need to be allocated on various Physical Machines (PMs) in order to minimize resource wastage and increase energy efficiency. Resource allocation problem is NP-hard. Hence finding an exact solution is complicated especially for large-scale datacenters. In this context, this paper proposes an Energy-oriented Flower Pollination Algorithm (E-FPA) for VM allocation in cloud datacenter environments. A system framework for the scheme was developed to enable energy-oriented allocation of various VMs on a PM. The allocation uses a strategy called Dynamic Switching Probability (DSP). The framework finds a near optimal solution quickly and balances the exploration of the global search and exploitation of the local search. It considers a processor, storage, and memory constraints of a PM while prioritizing energy-oriented allocation for a set of VMs. Simulations performed on MultiRecCloudSim utilizing planet workload show that the E-FPA outperforms the Genetic Algorithm for Power-Aware (GAPA) by 21.8%, Order of Exchange Migration (OEM) ant colony system by 21.5%, and First Fit Decreasing (FFD) by 24.9%. Therefore, E-FPA significantly improves datacenter performance and thus, enhances environmental sustainability.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Virtualization; Green computing; Cloud; Datacentre; Energy optimization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Schools and Research Institutes > School of Business and Technology > Technical & Applied Computing
Research Priority Areas: Applied Business & Technology
Depositing User: Susan Turner
Date Deposited: 02 May 2019 09:00
Last Modified: 07 May 2019 13:25
URI: http://eprints.glos.ac.uk/id/eprint/6797

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