دانلود Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition

فارسی Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition
قیمت : 355,000 ریال
شناسه محصول : 2008204
نویسنده/ناشر/نام مجله : Applied Soft Computing
سال انتشار: 2016
تعداد صفحات انگليسي : 16
نوع فایل های ضمیمه : pdf+word
حجم فایل : 1 Mb
کلمه عبور همه فایلها : www.daneshgahi.com
عنوان انگليسي : Comparative analysis of multi-objective evolutionary algorithms for QoS-aware web service composition

چکیده

Abstract

Web service composition combines available services to provide new functionality. The various available services have different quality-of-service (QoS) attributes. Building a QoS-optimal web service composition is a multi-criteria NP-hard problem. Most of the existing approaches reduce this problem to a single-criterion problem by aggregating different criteria into a unique global score (scalarization). However, scalarization has some significant drawbacks: the end user is supposed to have a complete a priori knowledge of its preferences/constraints about the desired solutions and there is no guarantee that the aggregated results match it. Moreover, non-convex parts of the Pareto set cannot be reached by optimizing a convex weighted sum. An alternative is to use Pareto-based approaches that enable a more accurate selection of the end-user solution. However, so far, only few solutions based on these approaches have been proposed and there exists no comparative study published to date. This motivated us to perform an analysis of several state-of-the-art multi-objective evolutionary algorithms. Multiple scenarios with different complexities are considered. Performance metrics are used to compare several evolutionary algorithms. Results indicate that GDE3 algorithm yields the best performances on this problem, also with the lowest time complexity.

Keywords: Service composition Quality of service Real world services Multi-objective optimization
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