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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12974

Title: Energy‑efficient Nature‑Inspired techniques in Cloud computing datacenters
Authors: Joda Usman, Mohammed
Ismail, Abdul Samad
Abdul‑Salaam, Gaddafi
Chizari, Hassan
Kaiwartya, Omprakash
Yau Gital, Abdulsalam
Abdullahi, Muhammed
Aliyu, Ahmed
Idi Dishing, Salihu
Keywords: Cloud computing
Nature-Inspired techniques
Issue Date: Feb-2019
Publisher: Telecommunication Systems
Citation: Telecommunication Systems, 71, 275–302
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-efcient 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-efciency. Finally, potential research directions are identifed 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-efcient methods for Cloud computing datacenters.
Description: This article is published in Telecommunication Systems and also available at DOI: https://doi.org/10.1007/s11235-019-00549-9
URI: https://doi.org/10.1007/s11235-019-00549-9"
Appears in Collections:College of Science

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