Semantic description and matching of services for pervasive environments

With the evolution of the World Wide Web and the advancement of the electronic world, the diversity of available services is increasing rapidly.This raises new demands for the efficient discovery and location of heterogeneous services and resources in dynamically changing environments. The traditional approaches for service discovery such as UDDI, Salutation, SLP etc. characterise the services by using predefined service categories and fixed attribute value pairs and the matching techniques in these approaches are limited to syntactic comparisons based on attributes or interfaces. More recently with the popularity of Semantic Web technologies, there has been an increased interest in the application of reasoning mechanisms to support discovery and matching. These approaches provide important directions in overcoming the limitations present in the traditional approaches to service discovery. However, these still have limitations and have overlooked issues that need to be addressed; particularly these approaches do not have an effective ranking criterion to facilitate the ordering of the potential matches, according to their suitability to satisfy the request under concern. This thesis presents a semantic matching framework to facilitate effective discovery of device based services in pervasive environments. This offers a ranking mechanism that will order the available services in the order of their suitability and also considers priorities placed on individual requirements in a request during the matching process. The proposed approach has been implemented in a pervasive scenario for matching device-based services. The Device Ontology which has been developed as part of this research, has been used to describe the devices and their services. The retrieval effectiveness of this semantic matching approach has been formally investigated through the use of human participant studies and the experimental results have indicated that the results correlate well with human perception. The performance of the solution has also been evaluated, to explore the effects of employing reasoning mechanisms on the efficiency of the matching process. Specifically the scalability of the solution has been investigated with respect to the request size and the number of advertisements involved in matching.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A Semantic Approach for Description and Ranked Matching of Services in Pervasive Environments

With the recent developments in technology, new and diverse devices are being introduced into the pervasive world. This has raised new challenges for the discovery of devices and their services in dynamic environments. The existing approaches such as Jini [AOSJ99], UPnP [UPnP06], 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 of these approaches, there has been an increasing interest in the use of Semantic Web technologies to support the description and matching of services. This paper proposes a semantic matching framework to facilitate effective discovery of device based services in pervasive environments. This offers a ranking mechanism that will order the available services in the order of their suitability; the evaluation of the experimental results have indicated that the results correlate well with human perception

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

A Pragmatic Approach for the Semantic Description and Matching of Pervasive Resources

The increasing popularity of personal wireless devices has raised new demands for the efficient discovery of heterogeneous devices and services in pervasive environments. With the advancement of the electronic world, the diversity of available services is increasing rapidly. %This raises new demands for the efficient discovery and location of heterogeneous services and resources in dynamically changing environments. Traditional approaches for service discovery describe services at a syntactic level and the matching mechanisms available for these approaches are limited to syntactic comparisons based on attributes or interfaces. In order to overcome these limitations, there has been an increased interest in the use of semantic description and matching techniques to support effective service discovery. In this paper, we present a semantic matching approach to facilitate the discovery of device-based services in pervasive environments. The approach includes a ranking mechanism that orders services according to their suitability and also considers priorities placed on individual requirements in a request during the matching process. The solution has been systematically evaluated for its retrieval effectiveness and the results have shown that the matcher results agree reasonably well with human judgement. Another important practical concern is the efficiency and the scalability of the semantic matching solution. Therefore, we have evaluated the scalability of the proposed solution by investigating the variation in matching time in response to increasing numbers of advertisements and increasing request sizes, and have presented the empirical results

Semantic Description and Matching of Services for Pervasive Environments

With the evolution of the World Wide Web and the advancement of the electronic world, the diversity of available services is increasing rapidly. This raises new demands for the efficient discovery and location of heterogeneous services and resources in dynamically changing environments. The traditional approaches for service discovery such as UDDI, Salutation, SLP etc. characterise the services by using predefined service categories and fixed attribute value pairs and the matching techniques in these approaches are limited to syntactic comparisons based on attributes or interfaces. More recently with the popularity of Semantic Web technologies, there has been an increased interest in the application of reasoning mechanisms to support discovery and matching. These approaches provide important directions in overcoming the limitations present in the traditional approaches to service discovery. However, these still have limitations and have overlooked issues that need to be addressed; particularly these approaches do not have an effective ranking criterion to facilitate the ordering of the potential matches, according to their suitability to satisfy the request under concern. This thesis presents a semantic matching framework to facilitate effective discovery of device based services in pervasive environments. This offers a ranking mechanism that will order the available services in the order of their suitability and also considers priorities placed on individual requirements in a request during the matching process. The proposed approach has been implemented in a pervasive scenario for matching device-based services. The Device Ontology which has been developed as part of this research, has been used to describe the devices and their services. The retrieval effectiveness of this semantic matching approach has been formally investigated through the use of human participant studies and the experimental results have indicated that the results correlate well with human perception. The performance of the solution has also been evaluated, to explore the effects of employing reasoning mechanisms on the efficiency of the matching process. Specifically the scalability of the solution has been investigated with respect to the request size and the number of advertisements involved in matching

Semantic Resource Matching for Pervasive Environments: The Approach and its Evaluation

Technological advancements in the past decade have caused a large increase in the number and diversity of electronic devices that have appeared in the home and office and these devices offer an increasingly heterogeneous range of services. This has introduced new challenges for the dynamic discovery of services in pervasive environments. Several discovery mechanisms currently exist such as Salutation, SLP etc. to support service discovery in the device domain. However, these approaches characterise the services either by using predefined service categories and fixed attribute value pairs. Such descriptions are inflexible and difficult to extend to new concepts and characteristics, and since these descriptions do not describe devices or services at a conceptual level, no form of inferencing can be carried out on them. Hence the matching techniques in these approaches are limited to syntactic comparisons based on attributes or interfaces. More recently with the popularity of Semantic Web technologies, there has been an increased interest in the use of ontologies for service descriptions and the application of reasoning mechanisms to support discovery and matching. In this document, we present a semantic matching framework to facilitate effective discovery of device based services in pervasive environments. This offers a ranking mechanism that will order the available services in the order of their suitability; the evaluation of the experimental results have indicated that the results correlate well with human perception

Enhancing Grid Service Discovery with a Semantic Wiki and the Concept Matching Approach

An important challenge of realizing the vision of Grid computing that heterogeneous resources are shared in dynamic and multi-institutional virtual organization is that users need to locate, find, select and invoke appropriate Grid services on demand. However, at the current stage, both Grid resource description and discovery mechanisms are still at an immature stage. This paper presents a semantic solution for flexible Grid service discovery. The service description knowledge is collected by using a semantic wiki, and the proposed service matching approach compares the semantic content of user requests against service advertisements and provides a ranked list of candidate service. Based on them, a service information middleware has been developed and integrated into the service-oriented Grid environment, facilitating an enhanced Grid access for users

A pragmatic approach for the semantic description and matching of pervasive resources

There has been an increased interest in the use of semantic description and matching techniques, to support service discovery and to overcome the limitations in the traditional syntactic approaches. However, the existing semantic matching approaches lack certain desirable properties that must be present in an effective solution to support service discovery. We present a semantic description and matching approach to facilitate resource discovery in pervasive environments; the approach includes a ranking mechanism that orders services according to their suitability and also considers priorities placed on individual requirements in a request. The solution has been evaluated for its effectiveness and the results have shown that the matcher results agree reasonably well with human judgement. The solution was also evaluated for its efficiency/scalability and from the experimental results obtained; we can observe that for most practical situations, matching time can be considered acceptable for reasonable numbers of advertisements and request sizes. The proposed approach improves existing semantic matching solutions in several key aspects. Specifically; it presents an effective approximate matching and ranking criterion and incorporates priority consideration in the matching process. As shown in the evaluation experiments, these features significantly improves the effectiveness of semantic matching