Estimating Distances Using Neighborhood Intersection

Information about distances to other nodes in wireless sensor networks has proven advantageous not only for location discovery but is also helpful for context aware applications in general. In this paper we present a novel approach to distance estimation that does neither depend on special hardware nor on unreliable measurements of physical wireless communication properties. Instead, it is inspired by the observation that distant nodes have fewer neighbors in common than close ones and calculates distances from intersection cardinalities of sets of adjacent nodes. We discuss related work and present the new approach in detail including its mathematical foundations. A simulative performance analysis comprising different scenarios shows that our scheme yields competitive results.