Customized and Optimized Service Selection with ProtocolDB
Globe '09 Proceedings of the 2nd International Conference on Data Management in Grid and Peer-to-Peer Systems
System Models for Goal-Driven Self-management in Autonomic Databases
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
SLA-driven planning and optimization of enterprise applications
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Efficiently selecting the best web services
RED'09 Proceedings of the 2nd international conference on Resource discovery
An expressive and efficient solution to the service selection problem
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
A sampling-based approach to identify QoS for web service orchestrations
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
System models for goal-driven self-management in autonomic databases
Data & Knowledge Engineering
Search based software engineering: techniques, taxonomy, tutorial
Empirical Software Engineering and Verification
A transactional-qos driven approach for web service composition
RED'10 Proceedings of the Third international conference on Resource Discovery
Towards robust service compositions in the context of functionally diverse services
Proceedings of the 21st international conference on World Wide Web
Self-Optimization and Self-Stabilization in Autonomic Clouds
Concurrency and Computation: Practice & Experience
Adaptive MOEA/D for QoS-based web service composition
EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
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In Service Oriented Architecture, each application is often designed as a set of abstract services, which defines its functions. A concrete service(s) is selected at runtime for each abstract service to fulfill its function. Since different concrete services may operate at different Quality of Service measures, application developers are required to select an appropriate set of concrete services that satisfies a given Service Level Agreement when a number of concrete services are available for each abstract service. This problem, the QoS-aware service composition problem, is known NP-hard, which takes a significant amount of time and costs to find optimal solutions (optimal combinations of concrete services) from a huge number of possible solutions. This paper proposes an optimization framework, called $E^3$, to address the issue. By leveraging a multiobjective genetic algorithm, E3 heuristically solves the QoS-aware service composition problem in a reasonably short time. The algorithm E3 proposes can consider multiple SLAs simultaneously and produce a set of Pareto solutions, which have the equivalent quality to satisfy multiple SLAs.