Energy-efficient Nature-Inspired techniques in Cloud computing datacenters

Mohammed Joda Usman (), Abdul Samad Ismail (), Gaddafi Abdul-Salaam (), Hassan Chizari (), Omprakash Kaiwartya (), Abdulsalam Yau Gital (), Muhammed Abdullahi, Ahmed Aliyu () and Salihu Idi Dishing ()
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Mohammed Joda Usman: Universiti Teknology Malaysia
Abdul Samad Ismail: Universiti Teknology Malaysia
Gaddafi Abdul-Salaam: Kwame Nkrumah University of Science and Technology
Hassan Chizari: University of Gloucestershire
Omprakash Kaiwartya: Nottingham Trent University
Abdulsalam Yau Gital: Abubakar Tafawa Balewa Bauchi
Muhammed Abdullahi: Ahmadu Bello University Zaria
Ahmed Aliyu: Universiti Teknology Malaysia
Salihu Idi Dishing: Ahmadu Bello University Zaria

Telecommunication Systems: Modelling, Analysis, Design and Management, 2019, vol. 71, issue 2, No 9, 275-302

Abstract: Abstract Cloud computing is a systematic delivery of computing resources as services to the consumers via the Internet. Infrastructure as a Service (IaaS) is the capability provided to the consumer by enabling smarter access to the processing, storage, networks, and other fundamental computing resources, where the consumer can deploy and run arbitrary software including operating systems and applications. The resources are sometimes available in the form of Virtual Machines (VMs). Cloud services are provided to the consumers based on the demand, and are billed accordingly. Usually, the VMs run on various datacenters, which comprise of several computing resources consuming lots of energy resulting in hazardous level of carbon emissions into the atmosphere. Several researchers have proposed various energy-efficient methods for reducing the energy consumption in datacenters. One such solutions are the Nature-Inspired algorithms. Towards this end, this paper presents a comprehensive review of the state-of-the-art Nature-Inspired algorithms suggested for solving the energy issues in the Cloud datacenters. A taxonomy is followed focusing on three key dimension in the literature including virtualization, consolidation, and energy-awareness. A qualitative review of each techniques is carried out considering key goal, method, advantages, and limitations. The Nature-Inspired algorithms are compared based on their features to indicate their utilization of resources and their level of energy-efficiency. Finally, potential research directions are identified in energy optimization in data centers. This review enable the researchers and professionals in Cloud computing datacenters in understanding literature evolution towards to exploring better energy-efficient methods for Cloud computing datacenters.

Keywords: Cloud computing; Datacenters; Energy-efficiency; Nature-Inspired techniques (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11235-019-00549-9

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