Nearest-neighbour query processing with non-spatial predicates for service allocation in smart space environment

The extensive capability of sensors let sensors autonomously collect various information on smart objects and store them to the spatial database through the wireless sensor networks. Based on spatial database, location-dependent information services (LDISs) can supply the resources according to the user locations. In LDISs, nearest-neighbour queries which return the closest object around the query location is recognised as the key component for searching the easily accessible services in smart spaces. However, existing works only consider the Euclidean distance. Thus, they have limitations to provide user-centric services that require the consideration for not only the distance but also the status of smart objects. Motivated by the issues of nearest-neighbour queries, this study proposes the new type of query called specified nearest-neighbour (SNN). SNN query considers the status and the locations of smart objects. For the SNN, the authors suggest a novel signature-based R-tree (SR-tree) index structure that handles non-spatial information of objects efficiently. Further, the authors propose an SNN query processing technique. Finally, they evaluate the performance of the proposed algorithm in various circumstances. Performance results indicate that SNN algorithm with SR-tree outperforms the existing works in terms of computational cost and disk input/output (I/O).