JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Fulfilling the Web services promise
Communications of the ACM - E-services: a cornucopia of digital offerings ushers in the next Net-based evolution
Service-Level Agreements and Commercial Grids
IEEE Internet Computing
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
QoS computation and policing in dynamic web service selection
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
IEEE Internet Computing
Mapping Service-Level Agreements in Distributed Applications
IEEE Internet Computing
A Framework for Resource Allocation in Grid Computing
MASCOTS '04 Proceedings of the The IEEE Computer Society's 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Service-Oriented Computing: Key Concepts and Principles
IEEE Internet Computing
An approach for quality of service adaptation in service-oriented Grids: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A scalable approach to the partition of QoS requirements in unicast and multicast
IEEE/ACM Transactions on Networking (TON)
Optimal partition of QoS requirements with discrete cost functions
IEEE Journal on Selected Areas in Communications
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A complicated task running on the grid system is usually made up of many services, each of which typically offers a better service quality at a higher cost. Mapping service level agreements (SLA) optimally is to find the most appropriate quality level for each service, so that the overall SLA of a task is achieved at the minimum cost. This paper considers mapping execution time SLA in the case of the discrete cost function, which is an NP-hard problem. Due to the high computation complexity of mapping SLA, we propose a precomputation scheme that computes the selection of service levels in advance for every possible SLA requirement, which reduces the response time of a request greatly. The precomputation employs (1 + ε) approximation, and its solution for any time bound is at most (1 + ε) times larger than the optimal cost. Simulations show the superiority of (1 + ε) approximation compared with other methods.