Energy-efficient Nature-Inspired techniques in Cloud computing datacenters

Usman, Mohammed Joda, Ismail, Abdul Samad, Abdul-Salaam, Gaddafi, Chizari, Hassan ORCID: 0000-0002-6253-1822, Kaiwartya, Omprakash, Gital, Abdulsalam Yau, Abdullahi, Muhammed, Aliyu, Ahmed and Dishing, Salihu Idi (2019) Energy-efficient Nature-Inspired techniques in Cloud computing datacenters. Telecommunication Systems, 71 (2). pp. 275-302. doi:10.1007/s11235-019-00549-9

6841 Chizari (2019) Energy-Efficient Nature-Inspired Techniques in Cloud Computing Datacenters.pdf - Accepted Version
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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.

Item Type: Article
Article Type: Article
Uncontrolled Keywords: Cloud computing · Datacenters · Energy-efficiency · Nature-Inspired techniques
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, Computing and Social Sciences
Research Priority Areas: Applied Business & Technology
Depositing User: Anne Pengelly
Date Deposited: 13 May 2019 14:09
Last Modified: 31 Aug 2023 08:01

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