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无线多媒体传感器网络能源效率的稳健预测

Robust Forecasting for Energy Efficiency of Wireless Multimedia Sensor Networks.

作者信息

Wang Xue, Ma Jun-Jie, Ding Liang, Bi Dao-Wei

机构信息

State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing 100084, P. R. China.

出版信息

Sensors (Basel). 2007 Nov 15;7(11):2779-2807. doi: 10.3390/s7112779.

DOI:10.3390/s7112779
PMID:28903261
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3965238/
Abstract

An important criterion of wireless sensor network is the energy efficiency inspecified applications. In this wireless multimedia sensor network, the observations arederived from acoustic sensors. Focused on the energy problem of target tracking, this paperproposes a robust forecasting method to enhance the energy efficiency of wirelessmultimedia sensor networks. Target motion information is acquired by acoustic sensornodes while a distributed network with honeycomb configuration is constructed. Thereby,target localization is performed by multiple sensor nodes collaboratively through acousticsignal processing. A novel method, combining autoregressive moving average (ARMA)model and radial basis function networks (RBFNs), is exploited to perform robust targetposition forecasting during target tracking. Then sensor nodes around the target areawakened according to the forecasted target position. With committee decision of sensornodes, target localization is performed in a distributed manner and the uncertainty ofdetection is reduced. Moreover, a sensor-to-observer routing approach of the honeycombmesh network is investigated to solve the data reporting considering the residual energy ofsensor nodes. Target localization and forecasting are implemented in experiments.Meanwhile, sensor node awakening and dynamic routing are evaluated. Experimentalresults verify that energy efficiency of wireless multimedia sensor network is enhanced bythe proposed target tracking method.

摘要

无线传感器网络的一个重要标准是特定应用中的能源效率。在这个无线多媒体传感器网络中，观测数据来自声学传感器。针对目标跟踪的能量问题，本文提出了一种鲁棒预测方法，以提高无线多媒体传感器网络的能源效率。通过声学传感器节点获取目标运动信息，同时构建具有蜂窝配置的分布式网络。从而，多个传感器节点通过声学信号处理协同执行目标定位。一种结合自回归移动平均（ARMA）模型和径向基函数网络（RBFN）的新颖方法被用于在目标跟踪期间执行鲁棒的目标位置预测。然后根据预测的目标位置唤醒目标周围的传感器节点。通过传感器节点的委员会决策，以分布式方式执行目标定位并降低检测的不确定性。此外，研究了蜂窝网状网络的传感器到观测器路由方法，以考虑传感器节点的剩余能量来解决数据报告问题。在实验中实现了目标定位和预测。同时，对传感器节点唤醒和动态路由进行了评估。实验结果验证了所提出的目标跟踪方法提高了无线多媒体传感器网络的能源效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b17/3965238/876eb1216af6/sensors-07-02779f16.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b17/3965238/80cace1c8b25/sensors-07-02779f12.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b17/3965238/876eb1216af6/sensors-07-02779f16.jpg

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