As the usage and development of wireless sensor networks increases, problems related to these networks are becoming apparent. Dynamic deployment is one of the main topics that directly affects the performance of the wireless sensor networks. In this paper, biogeography-based optimization is applied to the dynamic deployment of static and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A binary detection model is considered to obtain realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the artificial bee colony algorithm, Homo-H-VFCPSO and stud genetic algorithm that are also population-based optimization algorithms. Results show biogeography-based optimization can be preferable in the dynamic deployment of wireless sensor networks.
Furthermore, Biogeography-Based Optimization (BBO) algorithm REF increases the coverage area of the network in static and mobile sensor nodes.
Dynamic Deployment of Wireless Sensor Networks by Biogeography Based Optimization Algorithm
J. Sensor and Actuator Networks
J. Sensor and Actuator Networks
Computer Science