ITERATIONS, FLARIUM

QoS-based web service selection is an active research area and has attracted many re- searchers. A lot of methods are proposed in previous work, such as workflow model, global planning strategy using linear programming, graph/tree approach, QoS based selection of semantic web services, etc. In this section, we briefly discuss the relationships between our work and existing methods.

Industrial standard specifications have been proposed to provide infrastructure for web services composition. Among them BPEL4WS (Business Process Execution Language for Web Services) is the most widely used language for process-based service composition. It describes the execution procedure and abstract process of workflow. Other specifications include E-Flow, BPML, etc. WSLA [16] provides a framework for specifying and mon- itoring Service Level Agreements (SLA) for Web Services. A WSLA document defines assertions of a service provider to perform a service according to agreed guarantees for IT-level and business process-level service quality parameters such as response time and throughput, and measures to be taken in case of deviation and failure to meet the asserted service guarantees.

However, these specifications only provide mechanisms to carry out local services se- lection in dynamic environment, and QoS optimization from a global view is not supported. Our work is based on these proposals and aims to provide a QoS-based and personalized

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services selection model for the underlying workflow.

Besides industrial standards, many prototypes have been developed to assist in services composition. In particular, SWORD [100] uses a rule-based engine to realize a composi- tion by existing web services; SELF-SERVE [31] proposes a declarative language to carry out service composition based on state-chart. But these projects only focus on planning or analyzing workflow process, and neither QoS criteria nor QoS optimization issues are addressed.

QoS-based service selection could be considered as a special case of the more general problem of global optimization. [42] presents a QoS model, addressing time, cost, and reli- ability dimensions. The model computes the quality of service for workflows automatically based on QoS attributes of an atomic task. In [144], the QoS of web services is computed using a muti-dimensional model, and the global QoS optimization is solved by linear pro- gramming techniques. In [140], authors present a QoS broker to maximize the user-defined utility value. In the broker, the optimized services selection is modeled as the Multiple Choice Knapsack Problem and the shorted path problem in graph theory. In [128], authors use an AND/OR tree structure to model the service composition problem. The procedure of service composition is implemented through tree traversal, and a heuristic-based search method is proposed to retrieve composite services with top-k QoS values. [125] uses a qualitative graphical representation of preference, CP-nets, to deal with services selection in terms of user preferences. However, these approaches can not handle the cases where there is no fully satisfying service available, and the personalization issue is not discussed either.

Several works are related to QoS-based selection of semantic web services. Specif- ically, DAML-S and ebXML provide well defined, computer-interpretable semantics for

web services. Reference [127] describes a QoS model using the Web Service Modeling Ontology. Also, the idea of QoS model extension has been presented by some researchers, such as [41], [74], etc. In [41], the extended QoS model includes generic and domain or business specific criteria and allows users to express their preferences. [74] models web service configurations, associated prices and preferences using utility function policy, and the optimal service selection combines declarative logic-based matching rules with linear programming optimization methods. However, these works do not solve the empty result problem either. Furthermore, although users’ interest is concerned, it is only based on one preference and thus infeasible for practical purpose. To the contrary, our model takes into account all QoS criteria factors and a relaxation strategy is applied to describe users’ comprehensive preference.

Another area related to this chapter is skyline query. For example, [37] proposed the skyline operator; [97] developed an optimal and progressive algorithm for skyline queries; [78] introduced a skyline framework for defining the semantics of selection and join queries on relational database. Inspired by these works, we use a relaxation-based approach to perform QoS-based web service selection.

4.7 Conclusions

In this chapter we studied the problem of service selection with QoS constraints. A novel QoS model was proposed to perform flexible service selection. Based on the presented model, we developed various algorithms for making service selection on individual and composite services, respectively. We also introduced a top-k ranking strategy to reflect a user’s personalized requirement. The performance of the algorithms has been evaluated, showing the proposed QoS model is an efficient and practical strategy to satisfy users’ QoS

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requirements. As part of on-going work, we are interested in improving performance of the QoS query algorithms, as well as investigating more complicated workflow patterns. We also plan to integrate exception handling mechanism into our model during personalized service selection.