Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
An analysis of a large scale habitat monitoring application
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Cyclops: in situ image sensing and interpretation in wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Cover Set Problem in Directional Sensor Networks
FGCN '07 Proceedings of the Future Generation Communication and Networking - Volume 01
An Adjustable Target Coverage Method in Directional Sensor Networks
APSCC '08 Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference
Energy Efficient Target-Oriented Scheduling in Directional Sensor Networks
IEEE Transactions on Computers
A virtual potential field based coverage algorithm for directional networks
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
An electrostatic field- based coverage-enhancing algorithm for wireless multimedia sensor networks
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
On coverage issues in directional sensor networks: A survey
Ad Hoc Networks
On coverage problems of directional sensor networks
MSN'05 Proceedings of the First international conference on Mobile Ad-hoc and Sensor Networks
IEEE Communications Magazine
Voronoi-based coverage improvement approach for wireless directional sensor networks
Journal of Network and Computer Applications
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Directional sensor network is composed of many directional sensor nodes. Unlike conventional sensors that always have an omni-angle of sensing range, directional sensors may have a limited angle of sensing range due to technical constraints or cost considerations. Therefore, it is possible that when a directional sensor node is randomly deployed and scattered in the environment, some interested targets cannot be covered even if these targets are located in the sensing range of the sensor. We propose a Maximum Coverage with Rotatable Sensors (MCRS) problem in which coverage in terms of the number of targets to be covered is maximized whereas the rotated angles of sensors are minimized. We present two distributed greedy algorithm solutions for the MCRS problem. Simulation results shows that to apply angle adjustment algorithm can enhance the coverage rate of the directional sensor network.