Energy-balanced backpressure routing for stochastic energy harvesting WSNs

Abstract

In Energy Harvesting Wireless Sensor Networks (EHWSNs), energy imbalance among sensor nodes is detrimental to network performance and battery life. Particularly, nodes that are closer to a data sink or have less energy replenishment tend to exhaust their energy earlier, leading to some sub-regions of the environment being left unmonitored. Existing research efforts focus on energy management based on the assumption that the energy harvesting process is predictable. Unfortunately, such an assumption is not practicable in real-world energy harvesting systems. With the consideration of the unpredictability of the harvestable energy, in this paper we adopt the stochastic Lyapunov optimization framework to jointly manage energy and make routing decision, which could help mitigate the energy imbalance problem. We develop an online policies, Energy-balanced Backpressure Routing Algorithm (EBRA) for lossless networks. EBRA is distributed, queuing stable and do not require explicit knowledge of the statistics of the energy harvesting. The simulation data shows that EBRA could achieve significantly higher performance in terms of energy balance than the existing scheme Original Backpressure Algorithm (OBRA).