A Fast Response Neighbor Discovery Algorithm in Low-Duty-Cycle Mobile Sensor Networks

Anquan Zhang, Dongming Xu
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Abstract

With the rapid development of the Internet of Things, wireless sensor network, one of its important supporting technologies, has attracted more and more attention. We will work in the low duty cycle wireless sensor network, called low duty cycle wireless sensor network. Neighbor discovery is the most initial but essential work in low duty cycle wireless sensor networks. Although some neighbor discovery algorithms can also achieve neighbor discovery, the average discovery delay is long, and it is difficult to achieve the ability to respond quickly. How to make the nodes in the network quickly realize neighbor discovery is a difficult problem in current research. This paper proposes a group-based fast-response neighbor discovery algorithm (GBFR, in short). At the beginning of the time period, the nodes search for their neighbors by sending a short beacon message, so that the nodes group in pairs. By exchanging neighbor work schedules, nodes know ahead of time some other grouped potential neighbors. Combining the relative distance-based algorithm and node movement, it can selectively recommend suitable neighbors so that nodes can wake up actively and determine whether they are neighbors, thereby speeding up neighbor discovery, reducing communication energy consumption, and improving network life. In this paper, a large number of simulation experiments show that the algorithm has achieved good results in reducing the discovery delay and network energy consumption.
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低占空比移动传感器网络中的快速响应邻居发现算法
随着物联网的快速发展,无线传感器网络作为物联网的重要支撑技术之一,越来越受到人们的关注。我们将工作在低占空比无线传感器网络中,称为低占空比无线传感器网络。在低占空比无线传感器网络中,邻居发现是最重要的工作。有些邻居发现算法虽然也能实现邻居发现,但平均发现延迟较长,难以达到快速响应的能力。如何使网络中的节点快速实现邻居发现是当前研究的一个难题。提出了一种基于分组的快速响应邻居发现算法(简称GBFR)。在时间段开始时,节点通过发送短信标消息搜索相邻节点,使节点成对分组。通过交换邻居工作时间表,节点可以提前知道其他分组的潜在邻居。将基于相对距离的算法与节点运动相结合,有选择地推荐合适的邻居,使节点主动唤醒并判断是否为邻居,从而加快邻居发现速度,降低通信能耗,提高网络寿命。本文通过大量的仿真实验表明,该算法在降低发现延迟和网络能耗方面取得了良好的效果。
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