Network lifetime maximization via sensor selection

In this paper we consider the state estimation carried over a sensor network. At each time step, only a subset of all sensors are selected to send their observations to the fusion center, where a Kalman filter is implemented to perform the state estimation. The sensors are selected to maximize the lifetime of the network while maintaining a desired quality of state estimation accuracy. We propose a heuristic algorithm, based on convex optimization, for approximately solve the problem. An example of sensor network monitoring a diffusion process is presented to further illustrate the efficiency of the algorithm, comparing it with a greedy maximum energy available first algorithm (MEA) algorithm.