Abstract
AbstractService selection problem refers to the selection of appropriate Web services from a large number of candidates in order to create complex composite services that can satisfy users’ quality-of-service (QoS) requirements. However, the existing services selection methods seldom consider the parallel relations between services as well as the dynamic changing of QoS. To combat these defects, a QoS-aware composite services selection model is presented based on an AND/OR graph model in this paper. The weight of edges is defined by considering QoS attributes, and one shorter path in the model is corresponding to the better service composition that satisfies the service request. Besides, the model is not only capable of dealing with sequence relations and fork relations between services, but also capable of dealing with parallel relations between services. And then a heuristic services selection algorithm is developed based on the framework of the ant colony optimization (ACO) to guide finding the path, a...
Highlights
Web services are defined as self-contained, selfdescribing, modular applications that can be published, located, and invoked across the Web
Fang et al.27 presented a novel global QoS optimizing and multi-objective Web services selection algorithm based on multi-objective ant colony optimization (MOACO) for the dynamic Web service composition; Liu et al.25 proposed an algorithm by integrating Max-Min Ant System into Culture algorithm framework to solve the problem of composite Web services selection
In order to improve these defects, this paper presents a QoS-aware composite services selection algorithm, which is based on the ant colony optimization and uses an AND/OR graph to model the composite service system
Summary
Web services are defined as self-contained, selfdescribing, modular applications that can be published, located, and invoked across the Web. Fang et al. presented a novel global QoS optimizing and multi-objective Web services selection algorithm based on multi-objective ant colony optimization (MOACO) for the dynamic Web service composition; Liu et al. proposed an algorithm by integrating Max-Min Ant System into Culture algorithm framework to solve the problem of composite Web services selection. A Dynamic Composite Web Services Selection Method and upper bound, the service’s QoS is degraded; the Case 3 is under the environment that the number of invocations is between the lower and upper bound, but service’s QoS remains unchanged when considering the interactive with the service providers who hope to do the business. We will present a Web service composition selection algorithm based on the ACO and the AND/OR graph model to adapt the dynamic variations of QoS.
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