TSR: Temporal Subspace Routing for Peer-to-Peer Data Sharing
Sasu Tarkoma · 2006
In this paper we present the temporal subspace routing (TSR) technique for peer-to-peer environments that al- lows transparent exchange of information defined using metadata and queries based on user interests. The system unifies generic semantic matching, routing, caching, and access control. The technique supports continuous queries that are matched against metadata profiles of remote resources. Both queries and profiles are defined as subspaces of a multi-dimensional content space. Matched objects may be downloaded or synchronized. We present a generic data structure with optimizations for matching in this environment and discuss several use cases where the system may be applied. The mechanism utilizes the covering relation between queries and profiles. This allows automatic taxonomies of downloaded profiles and queries. Our main application is peer- to-peer and ad hoc metadata-based resource and file sharing. I. INTRODUCTION In recent years, pervasive computing has become reality with millions of mobile phones and portable devices. A number of core technologies are needed in order to realize the intelligent and adaptive services of tomorrow. Efficient and intelligent data sharing and synchronization are basic properties of current and future applications, especially in pervasive environments. We are faced with the challenge of how to locate nearby important data items and keep them synchronized on different devices. In this paper we present the temporal subspace routing (TSR) technique for peer-to-peer environments that allows transparent exchange of information defined using metadata and queries based on user interests. The technique supports continuous queries that are matched against metadata profiles of remote resources. Both queries and profiles are defined as subspaces of a multi-dimensional content space. Matched objects may be downloaded or synchronized. We present a data structure with optimizations for matching covering queries in this environment and discuss several use cases where the system may be applied. The mechanism utilizes the covering relation between queries and profiles. This allows automatic taxonomies of downloaded profiles and queries. TSR supports profile caching, profile trailing, and query-defined views on distributed data.