Processing generalized k-nearest neighbor queries on a wireless broadcast stream

  • Authors:

  • HaRim Jung;Yon Dohn Chung;Ling Liu

  • Affiliations:

  • Department of Computer Science and Engineering, College of Information and Communication, Korea University, Seoul 136-713, Republic of Korea;Department of Computer Science and Engineering, College of Information and Communication, Korea University, Seoul 136-713, Republic of Korea;College of Computing, Georgia Institute of Technology, Atlanta, GA 30280, USA

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2012

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Abstract

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.