Abstract
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 language | English |
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Title of host publication | 2019 Big Data, Knowledge and Control Systems Engineering (BdKCSE) |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 6 |
ISBN (Electronic) | 978-1-7281-6481-6 |
ISBN (Print) | 978-1-7281-6482-3 |
DOIs | |
Publication status | Published - 27 Feb 2020 |
Event | Big Data, Knowledge and Control Systems Engineering 2019 - Sofia, Bulgaria Duration: 21 Nov 2019 → 22 Nov 2019 https://ieeexplore.ieee.org/servlet/opac?punumber=8977239 |
Conference
Conference | Big Data, Knowledge and Control Systems Engineering 2019 |
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Abbreviated title | BdKCSE |
Country/Territory | Bulgaria |
City | Sofia |
Period | 21/11/19 → 22/11/19 |
Internet address |
Keywords
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