QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Adaptive Service Composition in Flexible Processes
IEEE Transactions on Software Engineering
Fast approximation algorithms for knapsack problems
SFCS '77 Proceedings of the 18th Annual Symposium on Foundations of Computer Science
Towards Composition as a Service - A Quality of Service Driven Approach
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
IEEE Internet Computing
Optimizing the Tradeoff between Discovery, Composition, and Execution Cost in Service Composition
ICWS '11 Proceedings of the 2011 IEEE International Conference on Web Services
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Various algorithms have been proposed for the problem of quality-driven service composition. They differ by the quality of the resulting executable processes and by their processing costs. In this paper, we study the problem of service composition from an economical point of view and adopt the perspective of a Composition as a Service provider. Our goal is to minimize composition costs while delivering executable workflows of a specified average quality. We propose to dynamically select different composition algorithms for different workflow templates based upon template structure and workflow priority. For evaluating our selection algorithm, we consider two classic approaches to quality-driven composition, genetic algorithms and integer linear programming with different parameter settings. An extensive experimental evaluation shows significant gains in efficiency when dynamically selecting between different composition algorithms instead of using only one algorithm.