Maximizing Video Sensor Network Lifetime through Genetic Clustering

In this paper we propose a novel communication protocol for studying the upper bounds on the lifetime of a video sensor network. Such networks are typically small due to their cost. Also, video sensors may have different transmission rates and data aggregation is difficult. Sensors are organized into clusters and a linear programming model is introduced for calculating a cluster head rotation schedule. Unlike most other clustering algorithms, our algorithm maximizes the network lifetime rather than minimizing the energy dissipation of sensors. Compared with previous models, our approach allows non-uniform transmission rates. In addition, the new protocol can maximize the K-of-N network lifetime, which has not been studied by most previous approaches so far. We use a genetic algorithm to compute optimal cluster formations. Simulation results show that our model can extend the lifetime of a sensor network up to five times over that of existing approaches.