Continuous range k-nearest neighbor queries in vehicular ad hoc networks

A driver should constantly keep an eye on nearby vehicles in order to avoid collisions. Unfortunately, the driver often does not see nearby vehicles because of obstacles (e.g., other vehicles, trees, buildings, etc.). This paper introduces a novel type of query, called a continuous range k-nearest neighbor (CRNN) query, in vehicular ad hoc networks, and it presents a new approach to process such a query. Most existing solutions to continuous nearest neighbor (CNN) queries focus on static objects, such as gas stations and restaurants, while this work concentrates on CRNN queries over moving vehicles. This is a challenging problem due to the high mobility of the vehicles. The CRNN query has characteristics in common with continuous range (CR) and CNN queries. In terms of CNN queries, the proposed approach achieves the same goal as the existing solutions, which is to decide effectively on valid intervals during which the query result remains unchanged. The proposed scheme aims to minimize the use of wireless network bandwidth, the computational cost, and the local storage while preserving information on the continuous movement of vehicles within the broadcast range of a given vehicle. Extensive experimental results confirm the effectiveness and superiority of the proposed scheme in comparison with an existing method.

► Movement information is stored, broadcast, and managed instead of a transient current location.
► The proposed method minimizes the total number of disseminated reports.
► The proposed method preserves information on the continuous movement of a vehicle.
► An experimental evaluation shows the validity and effectiveness of the proposed method over the conventional solution.