Battery-aware scheduling in wireless mesh networks

Wireless mesh networks recently emerge as a flexible, low-cost and multipurpose networking platform with wired infrastructure connected to the Internet. A critical issue in mesh networks is to maintain network activities for a long lifetime with high energy efficiency. As more and more outdoor applications require long-lasting, high energy efficient and continuously-working mesh networks with battery-powered mesh routers, it is important to optimize the performance of mesh networks from a battery-aware point of view. Recent study in battery technology reveals that discharging of a battery is nonlinear. Batteries tend to discharge more energy than needed, and reimburse the over-discharged energy later if they have sufficiently long recovery time. Intuitively, to optimize network performance, a mesh router should recover its battery periodically to prolong the lifetime. In this paper, we introduce a mathematical model on battery discharging duration and lifetime for wireless mesh networks. We also present a battery lifetime optimization scheduling algorithm (BLOS) to maximize the lifetime of battery-powered mesh routers. Based on the BLOS algorithm, we further consider the problem of using battery powered routers to monitor or cover a few hot spots in the network. We refer to this problem as the Spot Covering under BLOS Policy problem (SCBP). We prove that the SCBP problem is NP-hard and give an approximation algorithm called the Spanning Tree Scheduling (STS) to dynamically schedule mesh routers. The key idea of the STS algorithm is to construct a spanning tree according to the BLOS Policy in the mesh network. The time complexity of the STS algorithm is O(r) for a network with r mesh routers. Our simulation results show that the STS algorithm can greatly improve the lifetime, data throughput and energy consumption efficiency of a wireless mesh network.