We describe a shared ontology called SOUPA -Standard

We describe a shared ontology called SOUPA -Standard

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Abstract-This paper presents a framework to address new data management challenges introduced by data-intensive, pervasive computing environments. These challenges include a spatio-temporal variation of data and data source availability, lack of a global catalog and schema, and no guarantee of reconnection among peers due to the serendipitous nature of the environment. An important aspect of our solution is to treat devices as semiautonomous peers guided in their interactions by profiles and context. The profiles are grounded in a semantically rich language and represent information about users, devices, and data described in terms of "beliefs," "desires," and "intentions." We present a prototype implementation of this framework over combined Bluetooth and Ad Hoc 802.11 networks and present experimental and simulation results that validate our approach and measure system performance.Index Terms-Mobile data management, pervasive computing environments, data and knowledge representation, profile-driven caching algorithm, profile driven data management, data-centric routing algorithm.

Abstract. The past few years have seen significant work in mobile data management, typically based on the client/proxy/server model. Mobile/wireless devices are treated as clients that are data consumers only, while data sources are on servers that typically reside on the wired network. With the advent of "pervasive computing" environments an alternative scenario arises where mobile devices gather and exchange data from not just wired sources, but also from their ethereal environment and one another. This is accomplished using ad-hoc connectivity engendered by Bluetooth like systems. In this new scenario, mobile devices become both data consumers and producers. We describe the new data management challenges which this scenario introduces. We describe the design and present an implementation prototype of our framework, MoGATU, which addresses these challenges. An important component of our approach is to treat each device as an autonomous entity with its "goals" and "beliefs", expressed using a semantically rich language. We have implemented this framework over a combined Bluetooth and Ad-Hoc 802.11 network with clients running on a variety of mobile devices. We present experimental results validating our approach and measure system performance.