An approach for QoS-aware service composition based on genetic algorithms

Abstract

Web services are rapidly changing the landscape of software engineering. One of the most interesting challenges introduced by web services is represented by Quality Of Service (QoS)-aware composition and late-binding. This allows to bind, at run-time, a service-oriented system with a set of services that, among those providing the required features, meet some non-functional constraints, and optimize criteria such as the overall cost or response time. In other words, QoS-aware composition can be modeled as an optimization problem.We propose to adopt Genetic Algorithms to this aim. Genetic Algorithms, while being slower than integer programming, represent a more scalable choice, and are more suitable to handle generic QoS attributes. The paper describes our approach and its applicability, advantages and weaknesses, discussing results of some numerical simulations.

A QoS-Aware Hyper-graph Based Method of Semantic Service Composition

“…In [13], the authors model the problem as a multi-choice 0-1 knapsack problem or a multi-constraint optimal path problem, and then compute optimal result according to the objective function. In addition, a genetic algorithm is proposed to address the problem in [3]. Although it is more inefficient than Integer Programming, it can deal with non-linear constraints.…”

“…Therefore, semantic web is introduced into Web Service technologies to support dynamic and automated tasks such as discovery, composition and execution. In recent years, how to composite services automatically have drawn lots of research attentions [3][4][5][6][7][8][9]. In this paper we proposed a QoS(Quality of Service)-aware hyper-graph based method for semantic Web Service Composition.…”

Pairwise testing of dynamic composite services

“…We extend this testing tool to develop a generic testing methodology to query end-to-end QoS of a web service. Related empirical studies of optimal QoS compositions make use of genetic programming in Canfora et al [3] and linear programming in Zeng et al [23]. These are dynamic techniques to choose the best possible atomic services and configurations for SLAs.…”

Optimizing QoS-Aware Semantic Web Service Composition

“…To measure semantic similarity, we use the concept of (functional) semantic link [4], defined as a semantic connection (i.e., part of data flow) between an output and an input parameter of two services. Web service compositions could thus be estimated 376 F. Lécué and ranked not only along well known non functional parameters such as Quality of Services (QoS) [5] but also along the dimension of semantic similarity as indicator of functional fit [6]. Considering semantics on connections of services is useful in case the information required and provided by services does not match perfectly in every data flow.…”

“…Most approaches in the literature addressing optimization in web service composition are based on Integer linear Programming (IP) e.g., [8]. However, IP approaches have been shown to have poor scalability [5] in terms of time taken to compute optimal compositions when the size of the initial set of services grows. Such a case can arise in the future semantic web, where a large number of semantic services will be accessible globally.…”