Efficient Evaluation of k-Range Nearest Neighbor Queries in Road Networks

A k-Range Nearest Neighbor (or kRNN for short) query in road networks finds the k nearest neighbors of every point on the road segments within a given query region based on the network distance. The kRNN query is significantly important for location-based applications in many realistic scenarios. For example, (1) the user's location is uncertain, i.e., user's location is modeled by a spatial region, and (2) the user is not willing to reveal her exact location to preserve her privacy, i.e., her location is blurred into a spatial region. However, the existing solutions for kRNN queries simply apply the traditional k-nearest neighbor query processing algorithm multiple times, which poses a huge redundant searching overhead. To this end, we propose an efficient kRNN query processing algorithm in this paper. Our algorithm (1) employs a shared execution approach to eliminate the redundant searching overhead, and (2) provides a parameter that can be tuned to achieve a tradeoff betwe...

• Type: Conference
• Year: 2010
• Where: MDM
• Authors: Jie Bao 0003, Chi-Yin Chow, Mohamed F. Mokbel, Wei-Shinn Ku
• Keywords: Communications, KRNN Query, MDM 2010, Query Processing Algorithm, Redundant Searching Overhead