A new polynomial-time algorithm for linear programming
Combinatorica
Multi-sensor fusion: fundamentals and applications with software
Multi-sensor fusion: fundamentals and applications with software
On the hardness of approximating minimization problems
Journal of the ACM (JACM)
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
Wireless Sensor Networks: Architectures and Protocols
Wireless Sensor Networks: Architectures and Protocols
Integrated coverage and connectivity configuration in wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
A stochastic set-covering location model for both ameliorating and deteriorating items
Computers and Industrial Engineering - Special issue: Selected papers from the 27th international conference on computers & industrial engineering
Uncertainty-aware and coverage-oriented deployment for sensor networks
Journal of Parallel and Distributed Computing
IEEE Transactions on Computers
Computer Networks: The International Journal of Computer and Telecommunications Networking
Energy-efficient coverage based on probabilistic sensing model in wireless sensor networks
IEEE Communications Letters
Coverage problems in sensor networks: A survey
ACM Computing Surveys (CSUR)
Computers and Operations Research
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
Verification of k-coverage on query line segments
Proceedings of the 17th International Database Engineering & Applications Symposium
Experiment design for parameter estimation in sensing models
WiFlex'13 Proceedings of the First international conference on Wireless Access Flexibility
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Coverage is a fundamental task in sensor networks. We consider the minimum cost point coverage problem and formulate a binary integer linear programming model for effective sensor placement on a grid-structured sensor field when there are multiple types of sensors with varying sensing quality and price. The formulation is general and can be adapted to handle situations where sensing is perfect, imperfect or uncertain, and the coverage requirements are differentiated. Unfortunately, the new model suffers from the intractability of the binary integer programming formulations. We therefore suggest approximation algorithms and heuristics. Computational results indicate that the heuristic based on Lagrangean relaxation outperforms the others in terms of solution quality.