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Minimising Loss-Induced Errors in Real Time Wireless Sensing by Avoiding Data Dependency

机译:通过避免数据依赖性,在实时无线传感中最小化损失引起的错误

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The use of local processing to reduce data transmission rates, and thereby power and bandwidth requirements, is common in wireless sensor networks. Achieving the minimum possible data rate, however, is not always the optimal choice when the effects of packet loss on overall measurement error are considered. This paper presents a case study from the area of wireless inertial motion capture, in which the best distributed processing strategy is shown to be that which minimises inter-packet data dependency, rather than overall data rate. Drawing on this result and further analysis, we identify questions that should be raised during the design process in order to understand the effects of packet loss on distributed signal processing tasks, decide whether the errors are acceptable for an application, and choose appropriate techniques to mitigate them if necessary.
机译:在无线传感器网络中使用本地处理以降低数据传输速率,从而降低数据传输速率和带宽要求。然而,当考虑丢包对整体测量误差的效果时,实现最低可能的数据速率并不总是最佳选择。本文介绍了无线惯性运动捕获区域的案例研究,其中最佳分布式处理策略被认为是最小化分组间数据依赖性的,而不是整体数据速率。绘制此结果和进一步的分析,我们识别在设计过程中应提出的问题,以了解分布式信号处理任务对分布式信号处理任务的影响,决定应用程序是否可接受,并选择适当的技术来减轻误差如有必要,他们。

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