On graphs on n vertices having an identifying code of cardinality ⌈log2(n + 1)⇸
Discrete Applied Mathematics
Asymptotically optimal transmission policies for large-scale low-power wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
MoteTrack: a robust, decentralized approach to RF-based location tracking
Personal and Ubiquitous Computing
Sequence-Based Localization in Wireless Sensor Networks
IEEE Transactions on Mobile Computing
New bounds on binary identifying codes
Discrete Applied Mathematics
Adaptive identification in graphs
Journal of Combinatorial Theory Series A
RAID '08 Proceedings of the 11th international symposium on Recent Advances in Intrusion Detection
Note: On the size of identifying codes in binary hypercubes
Journal of Combinatorial Theory Series A
An optimal result for codes identifying sets of words
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Improved bounds on identifying codes in binary Hamming spaces
European Journal of Combinatorics
Joint Monitoring and Routing in Wireless Sensor Networks Using Robust Identifying Codes
Mobile Networks and Applications
Modeling and evaluation of homing-pigeon based delay tolerant networks with periodic scheduling
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Expert Systems with Applications: An International Journal
Identification in Z2 using Euclidean balls
Discrete Applied Mathematics
Mobility adaptive CSMA/CA MAC for wireless sensor networks
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
MoteTrack: a robust, decentralized approach to RF-Based location tracking
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
Mobility Adaptive Energy Efficient and Low Latency MAC for Wireless Sensor Networks
International Journal of Handheld Computing Research
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We propose a novel framework for location detection with sensor networks, based on the theory of identifying codes. The key idea of this approach is to allow sensor coverage areas to overlap so that each resolvable position is covered by a unique set of sensors. In this setting, determining a sensor-placement with a minimum number of sensors is equivalent to constructing an optimal identifying code, an NP-complete problem in general. We, thus, propose and analyze new polynomial-time algorithms for generating irreducible (but not necessarily optimal) codes for arbitrary topologies. Our algorithms incorporate robustness properties that are critically needed in harsh environments. We further introduce distributed versions of these algorithms, allowing sensors to self-organize and determine a (robust) identifying code without any central coordination. Through analysis and simulation, we show that our algorithms produce nearly optimal solutions for a wide range of parameters. In addition, we demonstrate a tradeoff between system robustness and the number of active sensors (which is related to the expected lifetime of the system). Finally, we present experimental results, obtained on a small testbed, that demonstrate the feasibility of our approach.