Worst and Best-Case Coverage in Sensor Networks
IEEE Transactions on Mobile Computing
Efficient Deployment Algorithms for Ensuring Coverage and Connectivity ofWireless Sensor Networks
WICON '05 Proceedings of the First International Conference on Wireless Internet
The coverage problem in a wireless sensor network
Mobile Networks and Applications
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Data aggregation in wireless sensor networks using ant colony algorithm
Journal of Network and Computer Applications
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Communications Magazine
Hi-index | 12.05 |
A wireless sensor network is composed of a large number of sensor nodes that are densely deployed in a sensing environment. The effectiveness of the wireless sensor networks depends to a large extent on the coverage provided by the sensor deployment scheme. In this paper, we present a sensor deployment scheme based on glowworm swarm optimization (GSO) to enhance the coverage after an initial random deployment of the sensors. Each sensor node is considered as individual glowworms emitting a luminant substance called luciferin and the intensity of the luciferin is dependent on the distance between the sensor node and its neighboring sensors. A sensor node is attracted towards its neighbors having lower intensity of luciferin and decides to move towards one of them. In this way, the coverage of the sensing field is maximized as the sensor nodes tend to move towards the region having lower sensor density. Simulation results show that our GSO-based sensor deployment approach can provide high coverage with limited movement of the sensor nodes.