Abstract. 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. 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.

Abstract. 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. 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.

There are diverse sensor applications built into different personal devices, which have the ability to record data related to various aspects of the user. With the ever increasing popularity and lowering costs of such personal devices such as Smart Phones, collecting data from the mobile sensors available in these devices becomes feasible. A wealth of information can be gleaned from such data collected from these sensors which reveals various aspects of the individual's behaviour and activity. Existing approaches for analyzing such data mainly focuses on inferring semantic context and detecting associations from such data. For example, GPS enabled devices allow users to record their movements in the form of spatio-temporal stream points, and meaningful information can be extracted based on different research objectives.In this paper, we have investigated a computation framework in order to identify users' activity categories and their event's associations from GPS trajectory data. This framework has several progressive stages and is designed based on different approaches in each stage, which will facilitate to analyse people's everyday lifestyles that are related to outdoor behaviours. Moreover, we have proposed an approach to improve the performance of the semantic annotation process of this framework, by combining different sources of mobile sensor data (i.e. GPS and audio data). The proposed framework and approaches have been validated on actual data sets which include the Microsoft's Geolife data set and a data set collected by ourselves.

Abstract. 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.

Abstract-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.