Exploring the kNN Search on Broadcast Multi-dimensional Index Trees

Abstract

Data broadcasting provides an effective way to disseminate information in the wireless mobile environment using a broadcast channel. How to provide the service of the k nearest neighbors (kNN) search using data broadcasting is studied in this paper. Given a data set D and a query point p, the kNN search finds k data points in D closest to p. By assuming that the data is indexed by an R-tree, we propose an efficient protocol for kNN search on the broadcast R-tree in terms of the tuning time which is the amount of time spent listening to the broadcast, latency which is time elapsed between issuing and termination of the query, and memory usage on the clients. We last validate the proposed protocol by extensive experiments.