Efficient Grid Task-Bundle Allocation Using Bargaining Based Self-Adaptive Auction
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Cloudbus Toolkit for Market-Oriented Cloud Computing
CloudCom '09 Proceedings of the 1st International Conference on Cloud Computing
Algorithms and mechanisms for procuring services with uncertain durations using redundancy
Artificial Intelligence
A global benefit maximization task-bundle allocation
NPC'11 Proceedings of the 8th IFIP international conference on Network and parallel computing
Double auction-inspired meta-scheduling of parallel applications on global grids
Journal of Parallel and Distributed Computing
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As users increasingly require better quality of service from Grids, resource management and scheduling mechanisms have to evolve in order to satisfy competing demands on limited resources. Traditional schedulers for Grids are system centric and favour system performance over increasing user’s utility. On the other hand market oriented schedulers are price-based systems that favour users but are based solely on user valuations. This paper proposes a novel meta-scheduler that unifies the advantages of both the systems for benefiting both users and resources. In order to do that, we design a valuation metric for user’s applications and computational resources based on multi-criteria requirements of users and resource load. The meta-scheduler maps user applications to suitable distributed resources using a Continuous Double Auction (CDA). Through simulation, we compare our scheduling mechanism against other common mechanisms used by current meta-schedulers. The results show that our meta-scheduler mechanism can satisfy more users than the others while still meeting traditional system-centric performance criteria such as average load and deadline of applications