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Double auction-inspired meta-scheduling of parallel applications on global grids

Citation

Garg, SK and Venugopal, S and Broberg, J and Buyya, R, Double auction-inspired meta-scheduling of parallel applications on global grids, Journal of Parallel and Distributed Computing, 73, (4) pp. 450-464. ISSN 0743-7315 (2013) [Refereed Article]

Copyright Statement

Copyright 2013 Elsevier

DOI: doi:10.1016/j.jpdc.2012.09.012

Abstract

Meta-schedulers map jobs to computational resources that are part of a Grid, such as clusters, that in turn have their own local job schedulers. Existing Grid meta-schedulers either target system-centric metrics, such as utilisation and throughput, or prioritise jobs based on utility metrics provided by the users. The system-centric approach gives less importance to users’ individual utility, while the user-centric approach may have adverse effects such as poor system performance and unfair treatment of users. Therefore, this paper proposes a novel meta-scheduler, based on the well-known double auction mechanism that aims to satisfy users’ service requirements as well as ensuring balanced utilisation of resources across a Grid. We have designed valuation metrics that commodify both the complex resource requirements of users and the capabilities of available computational resources. Through simulation using real traces, we compare our scheduling mechanism with other common mechanisms widely used by both existing market-based and traditional meta-schedulers. The results show that our meta-scheduling mechanism not only satisfies up to 15% more user requirements than others, but also improves system utilisation through load balancing.

Item Details

Item Type:Refereed Article
Keywords:grid computing, resource allocation, meta-scheduling, auction
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:Computer Time Leasing, Sharing and Renting Services
Author:Garg, SK (Dr Saurabh Garg)
ID Code:93819
Year Published:2013
Web of Science® Times Cited:9
Deposited By:Computing and Information Systems
Deposited On:2014-08-19
Last Modified:2015-02-13
Downloads:0

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