Maximizing Network Lifetime for Estimation in Multi-Hop Wireless Sensor Networks
In this paper, we consider distributed estimation in energy-limited wireless sensor networks from lifetime-distortion perspective, where the goal is to maximize the network lifetime for a given distortion requirement. To take into account both local quantization and multi-hop transmission, which are essential to save transmission energy and thus prolong the network lifetime, the network lifetime maximization problem is formulated as a nonlinear programming (NLP) problem, where there are three factors needed to be optimized jointly: (i) source coding at each sensor, (ii) source throughput of each sensor, and (iii) multi-hop routing path. Furthermore, we show that this NLP problem can be decoupled without loss of optimality and reformulated as a linear programming (LP) problem. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.