Web services can be specified from two perspectives, namely functional and non-functional properties. Multiple services may possess the same function while vary in their non-functional properties, or called quality-of-service (QoS). QoS values are important criteria for service selection or recommendation. Most of the former works in web service selection and recommendation treat the QoS values as constants. However, QoS values of a service as perceived by a given user are intrinsically random variables because QoS value prediction can never be precise and there are always some unobserved random effects. In this work, we address the service selection problem by representing services' QoS values as discrete random variables with probability mass functions. The goal is to select a set of atomic services for composing a composite service such that the probability of satisfying constraints imposed on the composite service is high and the execution time is reasonable. Our proposed method starts with an initial web service assignment and incrementally adjusts it using simulated annealing. We conduct several experiments and the results show that our approach generally performs better than previous works, such as the integer programming method and the cost-driven method.

Although reuse is the main goal of SOA, composing existing services to realize different user requirements is still a difficult and time-consuming task. Research on workflow templates and design patterns can facilitate reuse and assist with the service composition task. Nevertheless, workflow templates are too specific, whereas design patterns may be too abstract; their effectiveness in assisting the composition process may be limited. In this paper, we propose a comprehensive service pattern model that is more flexible than workflow/service templates while allowing systematic instantiation into the concrete workflows. It can help ease the composition process and enable flexible pattern-based reuse.

There are two approaches to specifying the composition of Web services: orchestration and choreography. Previous works in Web services selection are mostly based on the orchestration model which focuses on the interactions with a single party. However, in many application scenarios, business goals are achieved by a number of pair-wise interactions among a set of Web services, and there does not exist a single entity that is in charge of selecting Web services for all tasks. Each Web service will autonomously perform Web services selection. In such a choreographic environment, we study the kind of information that each Web service should provide to its partner Web services and how each Web service should perform Web service selection so as to maximize the chance of successfully accomplishing a business goal. The proposed approach is evaluated by simulation, and the experimental results show that our proposed method is close to centralized method and better than the other two distributed Web services selection methods.

This paper studies the dynamic web service selection problem in a failure-prone environment, which aims to determine a subset of Web services to be invoked at run-time so as to successfully orchestrate a composite web service. We observe that both the composite and constituent web services often constrain the sequences of invoking their operations and therefore propose to use finite state machine to model the permitted invocation sequences of Web service operations. We assign each state of execution an aggregated reliability to measure the probability that the given state will lead to successful execution in the context where each web service may fail with some probability. We show that the computation of aggregated reliabilities is equivalent to eigenvector computation and adopt the power method to efficiently derive aggregated reliabilities. In orchestrating a composite Web service, we propose two strategies to select Web services that are likely to successfully complete the execution of a given sequence of operations. A prototype that implements the proposed approach using BPEL for specifying the invocation order of a web service is developed and served as a testbed for comparing our proposed strategies and other baseline Web service selection strategies.

Dynamic Web service selection refers to determining a subset of component Web services to be invoked so as to orchestrate a composite Web service. Previous work in Web service selection usually assumes the invocations of Web service operations to be independent of one another. This assumption however does not hold in practice as both the composite and component Web services often impose some orderings on the invocation of their operations. Such orderings constrain the selection of component Web services to orchestrate the composite Web service. We therefore propose to use finite state machine (FSM) to model the invocation order of Web service operations. We define a measure, called aggregated reliability, to measure the probability that a given state in the composite Web service will lead to successful execution in the context where each component Web service may fail with some probability. We show that the computation of aggregated reliabilities is equivalent to eigenvector computation. The power method is hence adopted to efficiently derive aggregated reliabilities. In orchestrating a composite Web service, we propose two strategies to select component Web services that are likely to successfully complete the execution of a given sequence of operations. Our experiments on a synthetically generated set of Web service operation execution sequences show that our proposed strategies perform better than the baseline random selection strategy.