Efficient proximity detection among mobile objects in road networks with self-adjustment methods

Given a set of moving clients as well as their friend relationships, a road network, and a distance threshold per friend pair, the proximity detection problem in road networks is to find each pair of friends such that the road network distance between them is within the given threshold. The problem of proximity detection is often encountered in friend-locator applications and massively multiplayer online games. Because of the limited battery power and bandwidth, it is better to develop a solution which incurs less communication cost. Hence, the main objective of this problem is to reduce the total communication cost. However, most of the existing proximity detection solutions focus on the Euclidean space but cannot be used in road network space; the solutions for road networks incur substantial communication costs. Motivated by this, we propose two types of solutions to solve the proximity detection problem in road networks. In the first type of solution, each mobile client is assigned with a mobile region of a fixed size. We design algorithms with a fixed radius for the client and server respectively, with the purpose of reducing unnecessary probing messages and update messages. Second, we present a self-tuning policy to adjust the radius of the mobile region automatically to minimize the communication cost. Experiments show that our second type of solution works efficiently and robust with a much lower communication cost with respect to various parameters. In addition, we present our server-side computational cost optimization techniques to reduce the total computational cost.