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 Type:	Refereed Article
Keywords:	grid computing, resource allocation, meta-scheduling, auction
Research Division:	Information and Computing Sciences
Research Group:	Distributed computing and systems software
Research Field:	Distributed systems and algorithms
Objective Division:	Information and Communication Services
Objective Group:	Information systems, technologies and services
Objective Field:	Information systems, technologies and services not elsewhere classified
UTAS Author:	Garg, SK (Dr Saurabh Garg)
ID Code:	93819
Year Published:	2013
Web of Science® Times Cited:	17
Deposited By:	Information and Communication Technology
Deposited On:	2014-08-19
Last Modified:	2018-01-31
Downloads:	0