Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2009-03-08
Proceedings of the 16th International Conference on Advanced Computing and Communication (ADCOM 2008, IEEE Press, New York, US
Computer Science
Distributed, Parallel, and Cluster Computing
9 pages
Scientific paper
The user-level brokers in grids consider individual application QoS requirements and minimize their cost without considering demands from other users. This results in contention for resources and sub-optimal schedules. Meta-scheduling in grids aims to address this scheduling problem, which is NP hard due to its combinatorial nature. Thus, many heuristic-based solutions using Genetic Algorithm (GA) have been proposed, apart from traditional algorithms such as Greedy and FCFS. We propose a Linear Programming/Integer Programming model (LP/IP) for scheduling these applications to multiple resources. We also propose a novel algorithm LPGA (Linear programming driven Genetic Algorithm) which combines the capabilities of LP and GA. The aim of this algorithm is to obtain the best metaschedule for utility grids which minimize combined cost of all users in a coordinated manner. Simulation results show that our proposed integrated algorithm offers the best schedule having the minimum processing cost with negligible time overhead.
Buyya Rajkumar
Garg Saurabh
Konugurthi Pramod
No associations
LandOfFree
A Linear Programming Driven Genetic Algorithm for Meta-Scheduling on Utility Grids does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A Linear Programming Driven Genetic Algorithm for Meta-Scheduling on Utility Grids, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Linear Programming Driven Genetic Algorithm for Meta-Scheduling on Utility Grids will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-496504