An Approach for Semantic Query Processing with UDDI

Luo, Jin; Montrose, Bruce; Kang, Min Woo

doi:10.1007/11575863_24

Cited by 9 publications

(9 citation statements)

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“…One of the most widely used protocols for publishing service is Universal Description, Discovery and Integration (UDDI) specification [5,42] that enables service specification to be advertised in a service registry. In our previous studies on the UDDI specification [41], we used the tModel to represent the QoS for web services discovery, selection, and composition.…”

Section: Web Service Selectionmentioning

confidence: 99%

A user centric service-oriented modeling approach

Cheng

Chao

et al. 2011

World Wide Web

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With rapid development of service-oriented architecture and cloud computing, web services have been widely employed on the Internet. Quality of Service (QoS) is a very important criterion for service consumers to measure and select services. The selection of web services with respect to non-functional QoS criteria can be considered as a Multiple Criteria Decision Making (MCDM) problem when multiple consumers need to share a number of services. This paper describes a new user centric service-oriented modeling approach which is featured by integrating fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Service Component Architecture (SCA) to facilitate web service selection and composition and to effectively satisfy a group of service consumers' subjective requirements and preferences in the dynamic environment. The main contribution of this method is able to translate a group of users' fuzzy requirements to services as well as model different levels of hardware and software as services to meet the requirements. We also design a simulated environment that includes 8*8 LED matrix on a circuit board that corresponds to an office with different appliances to demonstrate the dynamic service selection and binding. The simulation is used to assess the computational efficiency of the fuzzy TOPSIS method and the effectiveness of the proposed system.

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Section: Web Service Selectionmentioning

confidence: 99%

A user centric service-oriented modeling approach

Cheng

Chao

et al. 2011

World Wide Web

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“…This section briefly outlines some of the representative approaches for augmenting UDDI with semantic search capabilities. The focus is primarily on the approaches presented by Luo et al (2005aLuo et al ( , 2005b and Akkiraju et al (2007) since these applications were the most influential in the development of the sensor-based architecture presented in this paper. A rough classification of representative approaches for augmenting UDDI with semantic capabilities is shown in Figure 2.…”

Section: Approaches To Augment Uddi With Semanticsmentioning

confidence: 99%

“…Semantic UDDI Approaches Paolucci [Paolucci et al 2002a[Paolucci et al , 2002b Akkiraju [Akkiraju et al 2003] Srinivasan [Srinivasan et al 2004] External Semantic Schema Akkiraju [Akkiraju et al 2007] Luo [Luo et al 2005a[Luo et al , 2005b The architecture developed by Akkiraju et al (2007) uses a variety of techniques; hence, it is classified as an approach that uses multiple inheritance. This approach is composed of a generic web service proxy, constraint checker, dynamic binder and invoker, and semantic UDDI infrastructure.…”

Section: Internal Semantic Schemamentioning

confidence: 99%

“…The search capability that conforms to the UDDI specification lacks adequate support for semantic descriptions of web services, which is integral in the dynamic discovery and composition process (Paolucci et al, 2002a(Paolucci et al, , 2002bAkkiraju et al, 2003Akkiraju et al, , 2007Carman et al, 2003;Sivashanmugam et al, 2003;Pistore et al, 2004;Srinivasan et al, 2004;Luo et al, 2005aLuo et al, , 2005bPeer, 2005;Goodwin & Russomanno, 2007). UDDI's search capability is syntax based and relies solely on the Extensible Markup Language (XML), which enables syntactic but not semantic query without additional knowledge layers, such as those offered by the semantic web infrastructure.…”

Section: Introductionmentioning

confidence: 99%

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Ontology integration within a service‐oriented architecture for expert system applications using sensor networks

Goodwin

Russomanno

2009

Expert Systems

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This paper describes the development of an architecture for the discovery of sensor services leveraging ontology-based semantics in the search query. A prototype has been implemented based upon the architecture and can be used to support the development of expert system applications in which sensors of certain types, operational capabilities or physical properties are required to support applications within a network-centric environment. In the prototype, sensor services are listed in a registry that references a machineinterpretable ontology. The registry conforms to the Universal Discovery and Description Interface (UDDI) specification, but it is augmented with semantic matching via an ontology to increase the likelihood that relevant sensor services are discovered when needed by expert system applications.

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“…We represent DP services in terms of vectors by considering the composite relation between input, output, and semantic relations between input and output. Inspired by semantic query processing [28], [29], the distance between DP service vectors is computed by considering the semantic similarity between terms. Terms are defined in a domain ontology and are used in service specifications.…”

Section: Introductionmentioning

confidence: 99%

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Zhou

Sellami

Gaaloul

et al. 2013

IEEE Trans. Automat. Sci. Eng.

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In service-oriented computing, a user usually needs to locate a desired service for: (i) fulfilling her requirements or (ii) replacing a service, which disappears or is unavailable for some reasons, to perform an interaction. With the increasing number of services available within an enterprise and over the Internet, locating a service online may not be appropriate from the performance perspective, especially in large Internet-based service repositories. Instead, services usually need to be clustered according to their similarity. Thereafter, services in one or several clusters are necessary to be examined online during dynamic service discovery. In this paper, we propose to cluster data providing (DP) services using a refined fuzzy -means algorithm. We consider the composite relation between DP service elements (i.e., input, output, and semantic relation between them) when representing DP services in terms of vectors. A DP service vector is assigned to one or multiple clusters with certain degrees. In addition, we introduce some operations for managing service clusters, when new services emerge or existing services disappear or become unavailable. When grouping similar services into one cluster, while partitioning different services into different clusters, the capability of service search engine is improved significantly. We have prototyped our approach and the source code is freely available on the web. We have evaluated our clustering approach in different settings and the results are very promising.Note to Practitioners-DP services are common nowadays, and there are a huge number of DP services in the Internet-scale environment. Locating an appropriate DP service accurately and efficiently with respect to the requirements of a certain requestor is a challenging task. This work presents a novel clustering-oriented approach, which aims to group DP services into clusters offline leveraging the semantic description of these DP services, and provides operations for managing these clusters. The clustering procedure is conducted by means of a machine learning technique which is a refined fuzzy -means method. A DP service can be assigned to one or several clusters with certain degrees. DP service clusters constitute a cluster network. Operations are provided for facilitating the evolution of cluster network, when a DP service emerges or disappears sometime for some reason. A prototype has been implemented and the approach has been evaluated on two test collections of DP services considering factors impacting the efficiency. Our method can be readily used in industrial DP service repository for supporting DP service discovery and replacement.

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An Approach for Semantic Query Processing with UDDI

Cited by 9 publications

References 1 publication

A user centric service-oriented modeling approach

A user centric service-oriented modeling approach

Ontology integration within a service‐oriented architecture for expert system applications using sensor networks

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

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