Hybrid QoS model which consists of certain and uncertain expressions has strong power of semantic QoS description. For solving the hybrid QoS-aware semantic web service composition problem,this paper presents an Uncertain Multi-attribute decision making based Composition algorithm(UMC) . The UMC includes two parts. First,UMC-Core can be used to synthetically evaluate the hybrid service quality information. Second,UMC-DH(Distributed and Heuristic framework for UMC) aims at enhancing the run-time performance of UMC when the problem space increases. The simulation results show that the UMC has lower execution cost,higher approximation ratio and success ratio than other similar approaches.
In service oriented architecture(SOA) ,service composition is a promising way to create new services. However,some technical challenges are hindering the application of service composition. One of the greatest challenges for composite service provider is to select a set of services to instantiate composite service with endto-end quality of service(QoS) assurance across different autonomous networks and business regions. This paper presents an iterative service selection algorithm for quality driven service composition. The algorithm runs on a peer-to-peer(P2P) service execution environment―distributed intelligent service execution(DISE) ,which provides scalable QoS registry,dynamic service selection and service execution services. The most significant feature of our iterative service selection algorithm is that it can work on a centralized QoS registry as well as cross decentralized ones. Network status is an optional factor in our QoS model and selection algorithm. The algorithm iteratively selects services following service execution order,so it can be applied either before service execution or at service run-time without any modification. We test our algorithm with a series of experiments on DISE. Experimental results illustrated its excellent selection and outstanding performance.
