The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Probability and statistics with reliability, queuing and computer science applications
Probability and statistics with reliability, queuing and computer science applications
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Neuro-Dynamic Programming
G-commerce: Market Formulations Controlling Resource Allocation on the Computational Grid
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
The Service Grid: Supporting Scalable Heterogeneous Services in Wide-Area Networks
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
Parallel computer workload modeling with markov chains
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
A stochastic control model for hierarchical grid service
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
A formal model for grid service deployment in grid service mining based on installation strategies
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
Maximal profit service task partition and distribution in computer grid
Computers and Industrial Engineering
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We introduce a formal model for deployment and hosting of a dynamic grid service wherein the service provider must pay a resource provider for the use of computational resources. Our model produces policies that balance the number of required resources with the desire to keep the cost of hosting the service to a minimum. The two components of cost that we consider are the deployment cost and the cost to keep the service active, which we view as a lease. We cast the problem in a dynamic programming framework and we are able to show that the model makes good leasing decisions in the face of such uncertainties as random demand for the service and random execution times of service requests. The results show that the policies obtained from the model reduce the cost of hosting a service and significantly reduce the variance of that cost.