Localization and identification in networks using robust identifying codes

Abstract

Abstract-Many practical problems in networks such as fault detection and diagnosis, location detection, environmental monitoring, etc, require to identify specific nodes or links based on a set of observations, which size is a subject of optimization. In this paper we focus on a combinatorial approach to these problems, which is closely related to coding techniques, and specifically to identifying codes. The identifying code problem for a given graph involves finding a minimum set of vertices whose neighborhoods uniquely overlap at any given graph vertex. In this paper we show efficient reductions between the identifying code problem and well-known covering problems, resulting in a tight hardness of approximation result and provable good centralized and distributed approximations. We further provide empirical and theoretical results on identifying codes in random networks and efficient constructions of these codes in infinite grids.

Localization of WSN node based on Time of Arrival using Ultra wide band spectrum

“…The identifying code technique is based on identifying code construction (ID-code) algorithm [17]. In this technique, reference nodes are deployed in such a way as to ensure that every resolvable location is covered by a unique set of reference nodes.…”

“…In this technique, reference nodes are deployed in such a way as to ensure that every resolvable location is covered by a unique set of reference nodes. The algorithm runs on the deployment region that is G = (V,E) in which vertices V represent the different regions and the edges E represent radio connectivity between regions [17].…”

Joint monitoring and routing in wireless sensor networks using robust identifying codes

“…We begin with a presentation of a polynomial-time approximation algorithm with provable performance guarantees (initially introduced in [13][14][15]) for the minimum r-robust identifying code problem. Our algorithm, called rID − LOCAL, generates a robust identifying code whose size is guaranteed to be at most 1 + 2 log(n) times larger than the optimum, where n is the number of vertices (a sharper bound is provided in Section II).…”