A General Framework for Adjustable Neighbor Discovery in Wireless Sensor Networks
Zhaoquan Gu, Yuexuan Wang, Keke Tang, Chao Li, Mohan Li, Lihua Yin · 2019
Wireless sensor networks have been widely adopted in real-life applications. As one of the fundamental processes in constructing the network, neighbor discovery is to find out the existence of the nearby nodes. In order to enlarge the lifetime of each node, the nodes switch the radio OFF for most of the time, and only turn the radio ON for necessary communications. The fraction of time that the radio in ON is called duty cycle and low duty cycle schedule could help save energy. Most works focus on designing efficient discovery schedule under a pre-defined low duty cycle such that the neighboring nodes can discover each other in a short time. In this paper, we study a more practical problem where each node could adjust the duty cycle dynamically by the remaining energy or the subsequent tasks, which is referred to as adjustable neighbor discovery. We first propose a general framework to handle the problem, then present two distributed algorithms that can ensure the discovery between the neighboring nodes, no matter when they start and what duty cycle they choose. We also conduct simulations to evaluate the algorithms and the results corroborate our analyses.