A coverage-preserving node scheduling scheme for large wireless sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
An Incremental Self-Deployment Algorithm for Mobile Sensor Networks
Autonomous Robots
Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
The coverage problem in a wireless sensor network
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Low-coordination topologies for redundancy in sensor networks
Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Efficient Deployment Algorithms for Ensuring Coverage and Connectivity ofWireless Sensor Networks
WICON '05 Proceedings of the First International Conference on Wireless Internet
Deploying wireless sensors to achieve both coverage and connectivity
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Approximation Algorithms for Sensor Deployment
IEEE Transactions on Computers
IEEE Transactions on Computers
IEEE Transactions on Mobile Computing
Coverage problems in sensor networks: A survey
ACM Computing Surveys (CSUR)
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Sensors have been increasingly used for many ubiquitous computing applications such as asset location monitoring, visual surveillance, and human motion tracking. In such applications, it is important to place sensors such that every point of the target area can be sensed by more than one sensor. Especially, many practical applications require 3-coverage for triangulation, 3D hull building, and etc. Also, in order to extract meaningful information from the data sensed by multiple sensors, those sensors need to be placed not too close to each other--minimum separation requirement. To address the 3-coverage problem with the minimum separation requirement, our recent work (Kim et al. 2008) proposes two heuristic methods, so called, overlaying method and TRE-based method, which complement each other depending on the minimum separation requirement. For these two methods, we also provide mathematical analysis that can clearly guide us when to use the TRE-based method and when to use the overlaying method and also how many sensors are required. To make it self-contained, in this paper, we first revisit the two heuristic methods. Then, as an extension, we present an ILP-based optimal solution targeting for grid coverage. With this ILP-based optimal solution, we investigate how much close the two heuristic methods are to the optimal solution. Finally, this paper discusses the impacts of the proposed methods on real-deployed systems using two example sensor systems. To the best of our knowledge, this is the first work that systematically addresses the 3-coverage problem with the minimum separation requirement.