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ThinkMind // ADAPTIVE 2018, The Tenth International Conference on Adaptive and Self-Adaptive Systems and Applications // View article adaptive_2018_2_20_50010


Improvement of Self-optimizing in Selection and Composition of Services Using Reinforcement Learning Algorithm Based on Convex Hull

Authors:
Hadis Khorasaninasab Abbasi
Eslam Nazemi

Keywords: self-adaption; self-optimizing; service composition; Reinforcement Learning; convex hull

Abstract:
Abstract—Web services are implemented by using many atomic or composite services. In a dynamic environment, some Web services require to select a service with defined Quality of Services(QoS) through runtime adaptation in changeable environments. In alignment with user satisfaction requirements, in selection of services a tradeoff between QoS should be considered, especially at runtime adaptation in dynamic environments. There are many methods for service selection and composite services with priority of QoS, but they do not predict optimizing service composition in the large scale environment. A self-optimizing method just continually adjusts the control service's parameters that pass to other services. In this paper, in a self-optimizing method, the goal and the procedure for selection and composition of optimal services are proposed. It includes three parts, services are limited in a defined scope by convex hull algorithm and then the optimal services are chosen by the divide-and-conquer algorithm. The optimal service selection is as input parameter goes to service composition algorithm. The QoS metrics taken into account and measured for the optimal service include response time, availability, throughput and reliability. The simulation results show that the system user satisfaction gradually increases by about 10% compared with the results of previous methods and show that the execution time is comparatively decreased by half.

Pages: 44 to 52

Copyright: Copyright (c) IARIA, 2018

Publication date: February 18, 2018

Published in: conference

ISSN: 2308-4146

ISBN: 978-1-61208-610-1

Location: Barcelona, Spain

Dates: from February 18, 2018 to February 22, 2018

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