Exploiting limited density information towards near-optimal energy balanced data propagation

In this work, we investigate the problem of achieving energy-balanced data propagation in a distributed wireless sensor network. The energy balance property is essential for prolonging the network lifetime by maximizing the functional lifetime of a large portion of sensors. We propose a distributed, adaptive data propagation algorithm that exploits limited, local density information for achieving energy-balanced propagation while at the same time keeping energy dissipation at low levels. Apart from traditional studies considering uniform sensor distribution, we investigate heterogeneous sensor placement distributions. We conduct a detailed experimental evaluation and comparison with state-of-the-art energy-balanced protocols in order to demonstrate that our density-based protocol improves energy efficiency significantly while also having better energy balance properties. To illustrate that our protocol has near-optimal performance, we compare our protocol with a centralized, off-line optimum solution derived by a linear program which maximizes the network lifetime and show that it achieves near-optimal performance for uniform sensor deployments.