A Relation Routing Scheme for Distributed Semantic Media Query

Performing complex semantic queries over large-scale distributed media contents is a challenging task for rich media applications. The dynamics and openness of data sources make it uneasy to realize a query scheme that simultaneously achieves precision, scalability, and reliability. In this paper, a novel relation routing scheme (RRS) is proposed by renovating the routing model of Content Centric Network (CCN) for directly querying large-scale semantic media content. By using proper query model and routing mechanism, semantic queries with complex relation constrains from users can be guided towards potential media sources through semantic guider nodes. The scattered and fragmented query results can be integrated on their way back for semantic needs or to avoid duplication. Several new techniques, such as semantic-based naming, incomplete response avoidance, timeout checking, and semantic integration, are developed in this paper to improve the accuracy, efficiency, and practicality of the proposed approach. Both analytical and experimental results show that the proposed scheme is a promising and effective solution for complex semantic queries and integration over large-scale networks.