Close-to-Optimal Energy Balanced Data Propagation Via Limited, Local Network Density Information
The authors study the problem of energy-balanced data propagation in wireless sensor networks. The energy balance property is crucial for maximizing the time the network is functional, by avoiding early energy depletion of a large portion of sensors. They propose a distributed, adaptive data propagation algorithm that exploits limited, local network density information for achieving energy-balance while at the same time minimizing energy dissipation. They investigate both uniform and heterogeneous sensor placement distributions. By a detailed experimental evaluation and comparison with well-known energy-balanced protocols, they show that their density-based protocol improves energy efficiency significantly while also having better energy balance properties.