Optimal precomputation for mapping service level agreements in grid applications
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Autonomic QoS-Aware resource management in grid computing using online performance models
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Heuristic solutions to resource allocation in grid computing: a natural approach
The Journal of Supercomputing
Optimal precomputation for mapping service level agreements in grid computing
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CBSE '08 Proceedings of the 11th International Symposium on Component-Based Software Engineering
Autonomic QoS control in enterprise Grid environments using online simulation
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A Min-Min average algorithm for scheduling transaction-intensive grid workflows
AusGrid '09 Proceedings of the Seventh Australasian Symposium on Grid Computing and e-Research - Volume 99
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Journal of Parallel and Distributed Computing
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QoS-Driven grid resource selection based on novel neural networks
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
Proceedings of the 7th International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks
International Journal of Distance Education Technologies
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Grid computing is the future computing paradigm for enterprise applications. An enterprise application running ongrid is composed of a set of SLA-constrained sub-tasks demanding different types of services and resources such as processors, data storages, service providers, and network links. This paper formalizes the resource allocation problem for SLA-constrained grid applications. The paper considers a very general case in which applications are decomposed into tasks that exhibit precedence relationships. The problem consists in finding the optimal resource allocation that minimizes total cost while preserving execution time service level agreements. The paper provides a framework for building heuristic solutions for this NP-hard problem, presents an example of such heuristic, and provides a numerical example.