Abstract

In a kNN query processing method, it is important to appropriately estimate the range that includes kNNs. While the range could be estimated based on the node density in the entire network, it is not always appropriate because the density of nodes in the network is not uniform. In this paper, we propose two kNN query processing methods in MANETs where the density of nodes is ununiform; the One-Hop (OH) method and the Query Log (QL) method. In the OH method, the nearest node from the point specified by the query acquires its neighbors' location and then determines the size of a circle region (the estimated kNN circle) which includes kNNs with high probability. In the QL method, a node which relays a reply of a kNN query stores the information on the query result for future queries.

Highlights

  • A location-based service (LBS) [15] is a typical application in mobile ad hoc networks (MANETs) [1, 2,7,10,13,16,19,25]

  • In the OH method, the global coordinator acquires its neighbors’ information by exchanging messages to know the density of nodes near the query point

  • The global coordinator sets the radius of the estimated k nearest neighbor (kNN) circle based on the density of nodes within its communication range and acquires the information on nodes within the estimated kNN circle

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Summary

Introduction

A location-based service (LBS) [15] is a typical application in mobile ad hoc networks (MANETs) [1, 2,7,10,13,16,19,25]. In an LBS, it is common that a node issues queries to search information on a specific location held by a mobile node in real time. In such a case, it is effective to process the queries as k nearest neighbor (kNN) queries, which search the information on the k nearest neighbors (kNNs) from a specified location (query point) [4,6,14,17,21,26,27,28]. Each node that received the query replies with the information on itself to the global coordinator, and the global coordinator sends back kNNs to the query-issuing node

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