In this paper, we investigate the problem of processing generalized k-nearest neighbor (GkNN) queries, which involve both spatial and non-spatial specifications for data objects, in a wireless broadcasting system. We present a method for processing GkNN queries on the broadcast stream. In particular, we propose a novel R-tree variant index structure, called the bit-vector R-tree (bR-tree), which stores additional bit-vector information to describe non-spatial attribute values of the data objects. In addition, each node in the bR-tree stores only one pointer to its children, which makes the bR-tree compact. We generate the broadcast stream by multiplexing the bR-tree and the data objects in the broadcasting channel. The corresponding search algorithm for the broadcast stream is also described. Through a series of comprehensive simulation experiments, we prove the efficiency of the proposed method with regard to energy consumption, latency, and memory requirement, which are the major performance concerns in a wireless broadcasting system. Furthermore, we test the practicality of the proposed method in a real prototype system.
Bibliographical noteFunding Information:
This work was supported by a Grant from the Korea Research Foundation , funded by the Korean Government ( KRF-2008-313-D00856 ).
- Generalized k-nearest neighbor (GkNN) queries
- Location-based services
- Mobile databases
- Wireless broadcasting systems
ASJC Scopus subject areas
- Theoretical Computer Science
- Control and Systems Engineering
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence