Context aware improve automatic discovery with

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Context-aware Improve automatic discovery with context analysis. Adapt to the environment changes. The analysis is complicated in the real world because the context is a general concept. Semantic-based Agent-based Facilitates dynamic rediscovering in the case of service fail. Can deal with incomplete service description info Need reasoning analysis. Ontology-based Facilitate automation of web service discovery. Improve discover similar semantic services. Need intensive domain knowledge. Different description languages lead to difficulty for users. Peer-2-peer Avoid central bottleneck. Routing in unstructured p2p using flooding causes network traffic. 4.3 Service Selection The increase in the number of available web services on the internet led to the increase in the similarity of service functionality offered by different providers each with different QoS parameters. Therefore, the selection of the optimal atomic service to be combined with other services to perform complex composite service with the most satisfaction of QoS values is one of the significant requirements for service composition [35]. The input of service selection phase is the set of candidate services for various tasks involved in composition plan. A single candidate services set consists of services providing the same functionality offered by different providers through service QoS profile. Services in a set differ in non-functional properties such as QoS attribute values or user preferences. Moreover, a set may include services provided by the same provider who offers the exact service with different quality values to obtain satisfaction of most users. Various solutions related to service selection were proposed. Figure 5 illustrates the categorization of these solutions related to optimization-based methods and decision making based methods. Decision-making methods are based on selecting services among multiple alternative services that best-fit decision maker goals and constraints. However, with a large number of candidate services, the optimization method is more efficient where it attempt to maximize or minimize one or multiple attributes taking into account user constraints.
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International Journal on Web Service Computing (IJWSC), Vol.7, No.1, March 2016 12 Figure 5: Selection Method Classification 4.3.1 Optimization-based method The optimization method is performed based on two types: (i) local optimization where the best service is selected for the individual task involved in composition plan, and (ii) global selection of services to guarantee overall composition plan as a single unit. 4.3.1.1. Local optimization method The service selection with local optimization chooses the best service for the individual task without considering the other tasks in composition or QoS requirement for the overall composed service. In this method, the candidate services for each task are ranked according to specific QoS attributes using utility theory. The utility theory mapped each quality attribute to values in utility
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  • Spring '16
  • Sameh
  • International Journal, Web Services, Service-oriented architecture, semantic web services

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