Semantic Information Based Web Service Discovery

Web service discovery is an important part of Web service applications. With the increase of the Web services, there come the problems that we must face to. The technology of traditional Web service discovery is based on the matching foundation of key words by combining WSDL and UDDI standardization. However, it is short of the description of semantic information, which means a low level of intelligence. Thus, it leads to low exactness and completeness. In the light of this issue, the paper draws the concept of semantic information into the research of Web service discovery. Through WordNet, it expands service description, raises semantic information, and makes semantic match possible. The paper puts forward a model based on semantic for Web service discovery, analyzes the function structure and the relationship between component parts of the model, moreover, it describes the work flow of the model. At the same time, the paper enlarges UDDI information and gives a matching algorithm on the similarity calculation through semantic analysis when finding the matched service

Integrating Protein Data Resources through Semantic Web Services

Understanding the function of every protein is one major objective of bioinformatics. Currently, a large amount of information (e.g., sequence, structure and dynamics) is being produced by experiments and predictions that are associated with protein function. Integrating these diverse data about protein sequence, structure, dynamics and other protein features allows further exploration and establishment of the relationships between protein sequence, structure, dynamics and function, and thereby controlling the function of target proteins. However, information integration in protein data resources faces challenges at technology level for interfacing heterogeneous data formats and standards and at application level for semantic interpretation of dissimilar data and queries. In this research, a semantic web services infrastructure, called Web Services for Protein data resources (WSP), for flexible and user-oriented integration of protein data resources, is proposed. This infrastructure includes a method for modeling protein web services, a service publication algorithm, an efficient service discovery (matching) algorithm, and an optimal service chaining algorithm. Rather than relying on syntactic matching, the matching algorithm discovers services based on their similarity to the requested service. Therefore, users can locate services that semantically match their data requirements even if they are syntactically distinctive. Furthermore, WSP supports a workflow-based approach for service integration. The chaining algorithm is used to select and chain services, based on the criteria of service accuracy and data interoperability. The algorithm generates a web services workflow which automatically integrates the results from individual services.A number of experiments are conducted to evaluate the performance of the matching algorithm. The results reveal that the algorithm can discover services with reasonable performance. Also, a composite service, which integrates protein dynamics and conservation, is experimented using the WSP infrastructure

A Framework for Dynamic Web Services Composition

Dynamic composition of web services is a promising approach and at the same time a challenging research area for the dissemination of service-oriented applications. It is widely recognised that service semantics is a key element for the dynamic composition of Web services, since it allows the unambiguous descriptions of a service's capabilities and parameters. This paper introduces a framework for performing dynamic service composition by exploiting the semantic matchmaking between service parameters (i.e., outputs and inputs) to enable their interconnection and interaction. The basic assumption of the framework is that matchmaking enables finding semantic compatibilities among independently defined service descriptions. We also developed a composition algorithm that follows a semantic graph-based approach, in which a graph represents service compositions and the nodes of this graph represent semantic connections between services. Moreover, functional and non-functional properties of services are considered, to enable the computation of relevant and most suitable service compositions for some service request. The suggested end-to-end functional level service composition framework is illustrated with a realistic application scenario from the IST SPICE project

A Semantic Framework for Priority-based Service Matching in Pervasive Environments

The increasing popularity of personal wireless devices has raised new demands for the efficient discovery of heterogeneous devices and services in pervasive environments. The existing approaches such as Jini [1], UPnP [8], etc., describe services at a syntactic level and the matching mechanisms in these approaches are limited to syntactic comparisons based on attributes or interfaces. In order to overcome the limitations in these approaches, there has been an increased interest in the use of semantic description and matching techniques to support effective service discovery. This paper proposes a semantic matching approach which facilitates the discovery of device-based services in a pervasive environment; the approach provides a ranking facility that orders services according to their suitability and also considers priorities placed on individual requirements in a request during the matching process. The evaluation studies have shown that the matcher results correlate reasonably well with human judgement

Grid service discovery with rough sets

Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.The computational grid is evolving as a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilising grid facilities. This paper presents ROSSE, a Rough sets based search engine for grid service discovery. Building on Rough sets theory, ROSSE is novel in its capability to deal with uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct non-functional properties related to Quality of Service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximise user satisfaction in service discovery. ROSSE is evaluated in terms of its accuracy and efficiency in discovery of computing services

Semantic-driven matchmaking of web services using case-based reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services