Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms Plus Data Structures Equals Evolution Programs
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
A Bidding Protocol for Deploying Mobile Sensors
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Sensor deployment and target localization in distributed sensor networks
ACM Transactions on Embedded Computing Systems (TECS)
Power conservation and quality of surveillance in target tracking sensor networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Modeling and simulating coverage in sensor networks
Computer Communications
Mobile Networks and Applications
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Wireless sensor networks (WSNs) have been the subject of an important development during the last years. Most of the applications deployed over WSNs require strong coverage requirements, especially those related to the detection and tracking of distributed events. In this paper, we use the Voronoi tessellation of the region of interest to formulate and solve an evolutionary optimisation problem modelling the activation of the deployed sensors. The major idea behind our approach is to adapt the spatial sensor distribution to the local probability of target presence. We show, through the results of our experiments, that our method allows a non-uniform deployment of the sensor nodes, which is better suitable for tracking applications.