Abstract-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 make use of efficient and distributed algorithm for generating robust identifying codes, an NP-hard problem, with a logarithmic performance guarantee based on a reduction to the set kmulticover problem. We also show how this same identifyingcode 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.

The identifying code problem for a given graph involves finding a minimum set of vertices whose neighborhoods uniquely overlap at any given graph vertex. Initially introduced in 1998, this problem has demonstrated its fundamental nature through a wide variety of applications, such as fault diagnosis, location detection, and environmental monitoring, in addition to deep connections to information theory, superimposed and covering codes, and tilings. This work establishes efficient reductions between the identifying code problem and the well-known setcovering problem, resulting in a tight hardness of approximation result and novel, provably tight polynomial-time approximations. The main results are also extended to r-robust identifying codes and analogous set (2r + 1)-multicover problems. Finally, empirical support is provided for the effectiveness of the proposed approximations, including good constructions for well-known topologies such as infinite two-dimensional grids. Index TermsIdentifying codes, robust identifying codes, hardness of approximation, set cover, test cover, distributed algorithms.

Objective testing of centerline extraction accuracy in quantitative coronary angiography (QCA) algorithms is a very difficult task. Standard tools for this task are not yet available. We present a simulation tool that generates synthetic angiographic images of a single coronary artery with predetermined centerline and diameter function. This simulation tool was used creating a library of images for the objective comparison and evaluation of QCA algorithms. This technique also provides the means for understanding the relationship between the algorithms' performance and limitations and the vessel's geometrical parameters. In this paper, two algorithms are evaluated and the results are presented.

We experimentally investigate the benefits of multi-hop networking for intra-car data aggregation under the current state-of-the-art Collection Tree Protocol (CTP). We show how this protocol actively adjusts collection routes according to channel dynamics in various practical car environments, resulting in performance gains over single-hop aggregation. Throughout our experiments, we target traditional performance metrics such as delivery rate, number of transmissions per packet, and delay, and our results confirm, both qualitatively and quantitatively, that multi-hop communication can provide a reliable and robust approach for data collection within a car.

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.