Disjoint identifying-codes for arbitrary graphs

Identifying codes have been used in a variety of applications, including sensor-based location detection in harsh environments. The sensors used in such applications are typically battery powered making energy conservation an important optimization criterion for lengthening network lifetime. In this work we propose and develop the concept of disjoint identifying codes with the motivation of providing energy load-balancing in such systems. We also provide information-theoretic upper and lower bounds on the number of disjoint identifying codes in a given graph, and show that these bounds are asymptotically tight for a modification of Hadamard matrices. A version of this paper should be presented at the IEEE Symposium on Information on Information Theory 2005. I

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

Wireless Sensor Networks (WSNs) provide an important means of monitoring the physical world, but their limitations present challenges to fundamental network services such as routing. In this work we utilize an abstraction of WSNs based on the theory of identifying codes. This abstraction has been useful in recent literature for a number of important monitoring problems, such as localization and contamination detection. In our case, we use it to provide a joint infrastructure for efficient and robust monitoring and routing in WSNs. Specifically, we provide an efficient and distributed algorithm for generating robust identifying codes with a logarithmic performance guarantee based on a novel reduction to the set k-multicover problem; to the best of our knowledge, this is the first such guarantee for the robust identifying codes problem, which is known to be NP-hard. We also show how this same identifying-code infrastructure provides a natural labeling that can be used for near-optimal routing with very small routing tables. We provide experimental results for various topologies that illustrate the superior performance of our approximation algorithms over previous identifying code heuristics

Fast data access over asymmetric channels using fair and secure bandwidth sharing

secure bandwidth sharin

Identifying Codes and the Set Cover Problem

We consider the problem of finding a minimum identifying code in a graph, i.e., a designated set of vertices whose neighborhoods uniquely overlap at any vertex on the graph. This identifying code problem was initially introduced in 1998 and has been since fundamentally connected to a wide range of applications, including fault diagnosis, location detection, environmental monitoring, and connections to information theory, superimposed codes, and tilings. Though this problem is NP-complete, its known reduction is from 3-SAT and does not readily yield an approximation algorithm. In this paper we show that the identifying code problem is computationally equivalent to the set cover problem and present a Θ(log n)-approximation algorithm based on the greedy approach for set cover; we further show that, subject to reasonable assumptions, no polynomial-time approximation algorithm can do better. Finally, we show that a generalization of the identifying codes problem, for which no complexity results were known thusfar, is NP-hard.