Abstract

Web services make tools which used to be merely accessible to the specialist available to all, and permitting previous manual data processing and analysis tasks to be automated. One of key problem is Web services composition in terms of Quality of Service (QoS). There are many task concurrencies, such as remote sensing image processing, in computation-intensive scientific applications. However, existing Web service optimal combination approaches are mainly focused on single tasks by using "selfish" behavior to pursue optimal solutions. This causes conflicts because many concurrent tasks are competing for limited optimal resources, and the reducing of service quality in services. Based on the best reply function of quantified task conflicts and game theory, this paper establishes a mathematical model to depict the competitive relationship between multitasks and Web service under QoS constraints and it guarantees that every task can obtain optimal utility services considering other task combination strategies. Moreover, an iterative algorithm to reach the Nash equilibrium is also proposed. Theory and experimental analysis show the approach has a fine convergence property, and can considerably enhance the actual utility of all tasks when compared with existing Web services combinatorial methods. The proposed approach provides a new path for QoS-aware Web service with optimal combinations for concurrent tasks.

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