With the growth of Utility Grids and various Grid market infrastructures, the need for efficient and cost effective scheduling algorithms is also increasing rapidly, particularly in the area of meta-scheduling. In these environments,users not only may have conflicting requirements with other users, but also they have to manage the trade-off between time and cost such that their applications can be executed most economically in the minimum time. Thus, choosing of the best Grid resources becomes a challenge in such a competitive market. This paper presents two novel heuristics for scheduling parallel applications on Utility Grids that manage and optimize the trade-off between time and cost constraints. The performance of the heuristics is evaluated through extensive simulations of a real-world environment with real parallel workload models to demonstrate the practicality of our algorithms. We compare our scheduling algorithms against other common algorithms used by current meta-schedulers. The results shows that our algorithms outperform other algorithms by minimizing the time and cost of application execution on Utility Grids.

Item Type:	Refereed Conference Paper
Keywords:	grid market, scheduling, meta-broker, cost
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:	93890
Year Published:	2009
Deposited By:	Information and Communication Technology
Deposited On:	2014-08-20
Last Modified:	2014-12-08
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