A collaborative approach to moving kk-nearest neighbor queries in directed and dynamic road networks

In this paper, we investigate a new approach to moving kk-nearest neighbor (MkkNN) queries in directed and dynamic road networks, where each road segment has a particular orientation and its travel time changes depending on traffic conditions. An MkkNN query continuously finds the kk nearest neighbors (NNs) of a moving query object. Most existing studies have focused on MkkNN queries in undirected and static road networks, where each road segment is bidirectional and its travel time does not change over time. However, little attention has been paid to MkkNN queries in directed and dynamic road networks. In this research, we propose COMET, a collaborative approach to Moving kk nEEaresTT neighbor queries in directed and dynamic road networks, where query processing is performed through collaboration between the server and query objects. In addition, we conduct extensive experiments to show that COMET substantially outperforms a conventional method in terms of query response time, bandwidth usage, and energy consumption.