Efficient algorithms for Web services selection with end-to-end QoS constraints

Abstract

Service-Oriented Architecture (SOA) provides a flexible framework for service composition. Using standard-based protocols (such as SOAP and WSDL), composite services can be constructed by integrating atomic services developed independently. Algorithms are needed to select service components with various QoS levels according to some application-dependent performance requirements. We design a broker-based architecture to facilitate the selection of QoS-based services. The objective of service selection is to maximize an application-specific utility function under the end-to-end QoS constraints. The problem is modeled in two ways: the combinatorial model and the graph model. The combinatorial model defines the problem as a multidimension multichoice 0-1 knapsack problem (MMKP). The graph model defines the problem as a multiconstraint optimal path (MCOP) problem. Efficient heuristic algorithms for service processes of different composition structures are presented in this article and their performances are studied by simulations. We also compare the pros and cons between the two models.

Service selection in mobile environments: considering multiple users and context-awareness

“…e.g. Alrifai et al, 2012; Yu et al, 2007; Zeng et al, 2004). When taking IUR into account, each user additionally has the possibility to specify a set of different IUR .…”

“…But existing works provide techniques to consider further control flow patterns like parallel, pick or conditional constructs (cf. Ardagna & Pernici, 2007; Yu et al, 2007), for instance, by using execution routes (cf. e.g.…”

“…without considering multiple users and context information), search for the optimal service composition for one single user under consideration of target weights and requirements regarding the NFP like price, availability, and so on (e.g. Alrifai, Risse, & Nejdl, 2012; Ardagna & Pernici, 2007; Yu, Zhang, & Lin, 2007; Zeng et al, 2004). At this, the service selection problem is usually formulated as knapsack optimisation problem (e.g.…”

“…At this, the service selection problem is usually formulated as knapsack optimisation problem (e.g. Alrifai & Risse, 2009; Alrifai et al, 2012; Yu et al, 2007). However, when considering multiple users and context information, we have to deal with the question how to model and integrate the resulting preference-based, context-based and temporal-based dependencies in terms of an optimisation-based approach.…”

“…Besides the target weights , user-defined requirements in terms of global end-to-end constraints regarding the NFP must be considered as well (e.g. Jin et al, 2012; Yu et al, 2007). …”