The design of service composition is one of the most challenging research problems in service-oriented computing. Building composite services is concerned with identifying a suitable set of services that orchestrated in some way is able to solve a business goal which cannot be resolved using a single service amongst those available. Despite the literature reports several approaches for (semi) automatic service composition, several problems, such as the capability of determining the composition's topology, still remain open. This paper proposes a search-based approach to semi-automatically support the design of service compositions. In particular the approach uses genetic programming to automatically generate workflows that accomplish a business goal and exhibit a given QoS level, with the aim of supporting the service integrator activities in the finalization of the workflow. © 2006 CRL Publishing Ltd.

A Genetic Programming Approach to Support the Design of Service Compositions

AVERSANO L;M DI PENTA;
2006-01-01

Abstract

The design of service composition is one of the most challenging research problems in service-oriented computing. Building composite services is concerned with identifying a suitable set of services that orchestrated in some way is able to solve a business goal which cannot be resolved using a single service amongst those available. Despite the literature reports several approaches for (semi) automatic service composition, several problems, such as the capability of determining the composition's topology, still remain open. This paper proposes a search-based approach to semi-automatically support the design of service compositions. In particular the approach uses genetic programming to automatically generate workflows that accomplish a business goal and exhibit a given QoS level, with the aim of supporting the service integrator activities in the finalization of the workflow. © 2006 CRL Publishing Ltd.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/234
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