IEEE Transactions on Computers
Probabilistic Coverage in Wireless Sensor Networks
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Deploying wireless sensors to achieve both coverage and connectivity
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Protecting with Sensor Networks: Attention and Response
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
A genetic algorithm for sensor deployment based on two-dimensional operators
Proceedings of the 2008 ACM symposium on Applied computing
On k-coverage in a mostly sleeping sensor network
Wireless Networks
Distributed Deployment Schemes for Mobile Wireless Sensor Networks to Ensure Multilevel Coverage
IEEE Transactions on Parallel and Distributed Systems
Energy-Efficient Protocol for Deterministic and Probabilistic Coverage in Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
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Wireless Sensor Networks (WSN) have been studied intensively for various applications such as monitoring and surveillance. Sensor deployment is an essential part of WSN, because it affects both the cost and capability of the sensor network. However, most deployment schemes proposed so far have been based on over-simplified assumptions, where results may be far from optimal in practice. Our proposal aims at automating and optimizing sensor deployment based on realistic topographic information, and is thus different from previous work in two ways: 1) it takes into account the 3D nature of the environment ; 2) it allows the use of anisotropic sensors. Based on the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the proposed approach shows good potential for tackling diverse problems in the WSN domain. Preliminary results are given for a mountainous area of North Carolina where coverage is maximized.