Distributed Progressive Algorithm for Maximizing Lifetime Vector in Wireless Sensor Networks

Maximizing the operational lifetime of a sensor network is a critical problem in practice. Many prior works define the network´s lifetime as the time before the first sensor in the network runs out of energy. However, when one sensor dies, the rest of the network can still work, as long as useful data generated by other sensors can reach the sink. More appropriately, we should maximize the lifetime vector of the network, consisting of the lifetimes of all sensors, sorted in ascending order. For this problem, there exists only a centralized algorithm that solves a series of linear programming problems with high-order complexities. This paper proposes a fully distributed progressive algorithm which iteratively produces a series of lifetime vectors, each better than the previous one. Instead of giving the optimal result in one shot after lengthy computation, the proposed distributed algorithm has a result at any time, and the more time spent gives the better result. We show that when the algorithm stabilizes, its result produces the maximum lifetime vector. Furthermore, simulations demonstrate that the algorithm is able to converge rapidly towards the maximum lifetime vector with low overhead.