Optimal load balancing in distributed computer systems
Optimal load balancing in distributed computer systems
An alternating offers bargaining model for computationally limited agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
An Extended Alternating-Offers Bargaining Protocol for Automated Negotiation in Multi-agent Systems
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
A Game-Theoretic Model and Algorithm for Load Balancing in Distributed Systems
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Optimizing Static Job Scheduling in a Network of Heterogeneous Computers
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
Negotiating Agents in a Market-Oriented Grid
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Price-based user-optimal job allocation scheme for grid systems
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Utilization-based pricing for power management and profit optimization in data centers
Journal of Parallel and Distributed Computing
A hybrid policy for fault tolerant load balancing in grid computing environments
Journal of Network and Computer Applications
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In this paper we propose two price-based job allocation schemes for computational grids. A grid system tries to solve problems submitted by various grid users by allocating the jobs to the computing resources governed by different resource owners. The prices charged by these owners are obtained based on a pricing model using a bargaining game theory framework. These prices are then used for job allocation. We present the grid system model and formulate the two schemes as a constraint minimization problem and as a non-cooperative game respectively. The objective of these schemes is to minimize the cost for the grid users. We present algorithms to compute the optimal load (job) fractions to allocate jobs to the computers. Finally, the two schemes are compared under simulations with various system loads and configurations and conclusions are drawn.