Resource management for deadline constrained MapReduce jobs for minimising energy consumption Online publication date: Fri, 28-Sep-2018
by Adam Gregory; Shikharesh Majumdar
International Journal of Big Data Intelligence (IJBDI), Vol. 5, No. 4, 2018
Abstract: Cloud computing has emerged as one of the leading platforms for processing large-scale data intensive applications. Such applications are executed in large clusters and data centres which require a substantial amount of energy. Energy consumption within data centres accounts for a considerable fraction of costs and is a significant contributor to global greenhouse gas emissions. Therefore, minimising energy consumption in data centres is a critical concern for data centre operators, cluster owners, and cloud service providers. In this paper, we devise a novel energy aware MapReduce resource manager for an open system, called EAMR-RM, that can effectively perform matchmaking and scheduling of MapReduce jobs each of which is characterised by a service level agreement (SLA) for performance that includes a client specified earliest start time, execution time, and a deadline with the objective of minimising data centre energy consumption. Performance analysis demonstrates that for a range of system and workload parameters experimented with the proposed technique can effectively satisfy SLA requirements while achieving up to a 45% reduction in energy consumption compared to approaches which do not consider energy in resource management decisions.
Online publication date: Fri, 28-Sep-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Big Data Intelligence (IJBDI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com