QoS-based service optimization using differential evolution

Authors:
Florin-Claudiu Pop;Denis Pallez;Marcel Cremene;Andrea Tettamanzi;Mihai Suciu;Mircea Vaida
Affiliations:
Technical University of Cluj-Napoca, Cluj-Napoca, Romania;University of Nice Sophia-Antipolis, Sophia-Antipolis, France;Technical University of Cluj-Napoca, Cluj-Napoca, Romania;Universita degli Studi di Milano, Milano, Italy;Babes Bolyai University of Cluj-Napoca, Cluj-Napoca, Romania;Technical University of Cluj-Napoca, Cluj-Napoca, Romania
Venue:
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Year:
2011

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Abstract

The aim of our research is to find an efficient solution to the services QoS optimization problem. This NP-hard problem is well known in the service-oriented computing field: given a business workflow that includes a set of abstract services and a set of concrete service implementations for each abstract service, the goal is to find the optimal combination of concrete services. The majority of recent proposals indicate the Genetic Algorithms (GA) as the best approach for complex workflows. But this problem usually needs to be solved at runtime, a task for which GA may be too slow. We propose a new approach, based on Differential Evolution (DE), that converges faster and it is more scalable and robust than the existing solutions based on Genetic Algorithms.