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Power optimisation model for leveraging cloud system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cloud computing is an emerging technology that has significantly increased over the years due to an increase in the number of internet users and its numerous benefits. It is a technology that leverages cost and considers locational challenges. The emergence of cloud computing has brought innovation and hope to many under-developed countries with less skilled workforce, limited resources and unstable electricity supply. Although this technology is transforming information technology, it still faces some significant challenges like high energy consumption rate, confusion in adoption method and security issues. The focus of this paper is on reducing the problems with ambiguity on data center structure and its power usage by simplifying how the application works and then provide a holistic approach to minimizing it power usage rate. This paper minimizes the energy utilization of the cloud data center using an intelligent method to shut down, schedule and monitors the entire cloud system. Additionally, observing the complexity of the cloud system design, a holistic approach to calculating and measuring the percise amount of power usage during each operational cycle is vital to achieving a more efficient data centre energy model. This work proposes an improved energy model that calculates, in detail, the energy usage on the system by focusing on each system component and its contribution to the high energy consumption level of the data centre. Furthermore, the proposed model is then used to develop an algorithm that minimises the power usage in the cloud environment to an optimal low level while maintaining high level of service level agreement. The result obtained from this experiment shows that the developed model removed a high level of obscurity in the issue of the cause of high energy consumption in the data center and thereby encourage cloud providers to act accordingly in reducing the effect.
Original languageEnglish
Title of host publication2019 Big Data, Knowledge and Control Systems Engineering (BdKCSE)
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-7281-6481-6
ISBN (Print)978-1-7281-6482-3
DOIs
Publication statusPublished - 27 Feb 2020
EventBig Data, Knowledge and Control Systems Engineering 2019 - Sofia, Bulgaria
Duration: 21 Nov 201922 Nov 2019
https://ieeexplore.ieee.org/servlet/opac?punumber=8977239

Conference

ConferenceBig Data, Knowledge and Control Systems Engineering 2019
Abbreviated titleBdKCSE
CountryBulgaria
CitySofia
Period21/11/1922/11/19
Internet address

Documents

  • paper ID 35-_ power optimization model for Leveraging Cloud System

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    Accepted author manuscript (Post-print), 478 KB, PDF document

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