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无线网络中用于估计时钟偏差和接收窗口选择的能量最小化算法

Energy Minimization Algorithm for Estimation of Clock Skew and Reception Window Selection in Wireless Networks.

作者信息

Gorawski Michał, Grochla Krzysztof, Marjasz Rafał, Frankiewicz Artur

机构信息

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, ul. Bałtycka 5, 44-100 Gliwice, Poland.

AIUT Sp. z o.o., Wyczółkowskiego 113, 44-100 Gliwice, Poland.

出版信息

Sensors (Basel). 2021 Mar 4;21(5):1768. doi: 10.3390/s21051768.

Abstract

The synchronization of time between devices is one of the more important and challenging problems in wireless networks. We discuss the problem of maximization of the probability of receiving a message from a device using a limited listening time window to minimize energy utilization. We propose a solution to two important problems in wireless networks of battery-powered devices: a method of establishing a connection with a device that has been disconnected from the system for a long time and developed unknown skew and also two approaches to follow-up clock synchronization using the confidence interval method. We start with the analysis of measurements of clock skew. The algorithms are evaluated using extensive simulations and we discuss the selection of parameters balancing between minimizing the energy utilization and maximizing the probability of reception of the message. We show that the selection of a time window of growing size requires less energy to receive a packet than using the same size of time window repeated multiple times. The shifting of reception windows can further decrease the energy cost if lower packet reception probability is acceptable. We also propose and evaluate an algorithm scaling the reception window size to the interval between the packet transmission.

摘要

设备之间的时间同步是无线网络中较为重要且具有挑战性的问题之一。我们讨论了在使用有限监听时间窗口以最小化能量利用的情况下,最大化从设备接收消息概率的问题。我们针对电池供电设备的无线网络中的两个重要问题提出了一种解决方案:一种与长时间与系统断开连接且产生未知偏差的设备建立连接的方法,以及两种使用置信区间方法进行后续时钟同步的方法。我们从对时钟偏差测量的分析开始。通过广泛的模拟对算法进行评估,并且我们讨论了在最小化能量利用和最大化消息接收概率之间平衡的参数选择。我们表明,选择大小不断增长的时间窗口来接收数据包比多次重复使用相同大小的时间窗口所需的能量更少。如果可以接受较低的数据包接收概率,接收窗口的移动可以进一步降低能量成本。我们还提出并评估了一种将接收窗口大小按数据包传输间隔进行缩放的算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4994/7961599/89c654496072/sensors-21-01768-g001.jpg

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