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Renewable energy-based multi-indexed job classification and container management scheme for sustainability of cloud data centers

Citation

Aujla, GS and Kumar, N and Garg, S and Kaur, K and Ranjan, R and Garg, SK, Renewable energy-based multi-indexed job classification and container management scheme for sustainability of cloud data centers, IEEE Transactions on Industrial Informatics pp. 1-11. ISSN 1551-3203 (2018) [Refereed Article]

Copyright Statement

Copyright 2018 IEEE

DOI: doi:10.1109/TII.2018.2800693

Abstract

Cloud Computing has emerged as one of the most popular technologies of the modern era for providing on-demand services to the end users. Most of the computing tasks in cloud data centers are performed by geo-distributed data centers which may consume hefty amount of energy for their operations. However, the usage of renewable energy resources with appropriate server selection and consolidation can mitigate the energy related issues in cloud environment. Hence, in this paper, we propose a renewable energy-aware multi-indexed job classification and scheduling scheme using Container as-a-Service (CoaaS) for data centers sustainability. In the proposed scheme, incoming workloads from different devices are transferred to the DC which has sufficient amount of renewable energy available with it. For this purpose, a renewable energy-based host selection and container consolidation scheme is also designed. The proposed scheme has been evaluated using Google workload traces. The results obtained prove 15%, 28% and 10.55% higher energy savings in comparison to the existing schemes of its category.

Item Details

Item Type:Refereed Article
Keywords:green computing, cloud computing
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Garg, SK (Dr Saurabh Garg)
ID Code:125152
Year Published:2018
Deposited By:Information and Communication Technology
Deposited On:2018-04-03
Last Modified:2018-06-28
Downloads:0

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