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. |
| Cite as: Garg, S.K., Buyya, R. and Siegel, H.J. (2009). Scheduling Parallel Applications on Utility Grids: Time and Cost Trade-off Management. In Proc. Thirty-Second Australasian Computer Science Conference (ACSC 2009), Wellington, New Zealand. CRPIT, 91. Mans, B., Ed. ACS. 139-147. |
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