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无线传感器网络的可靠性

Reliability of wireless sensor networks.

作者信息

Dâmaso Antônio, Rosa Nelson, Maciel Paulo

机构信息

Centro de Informática, Universidade Federal de Pernambuco, Recife, PE, 50740-560, Brazil.

出版信息

Sensors (Basel). 2014 Aug 25;14(9):15760-85. doi: 10.3390/s140915760.

DOI:10.3390/s140915760
PMID:25157553
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4208144/
Abstract

Wireless Sensor Networks (WSNs) consist of hundreds or thousands of sensor nodes with limited processing, storage, and battery capabilities. There are several strategies to reduce the power consumption of WSN nodes (by increasing the network lifetime) and increase the reliability of the network (by improving the WSN Quality of Service). However, there is an inherent conflict between power consumption and reliability: an increase in reliability usually leads to an increase in power consumption. For example, routing algorithms can send the same packet though different paths (multipath strategy), which it is important for reliability, but they significantly increase the WSN power consumption. In this context, this paper proposes a model for evaluating the reliability of WSNs considering the battery level as a key factor. Moreover, this model is based on routing algorithms used by WSNs. In order to evaluate the proposed models, three scenarios were considered to show the impact of the power consumption on the reliability of WSNs.

摘要

无线传感器网络(WSN)由数百个或数千个处理、存储和电池能力有限的传感器节点组成。有几种策略可以降低WSN节点的功耗(通过延长网络寿命)并提高网络的可靠性(通过改善WSN服务质量)。然而,功耗与可靠性之间存在内在冲突:可靠性的提高通常会导致功耗增加。例如,路由算法可以通过不同路径发送相同数据包(多路径策略),这对可靠性很重要,但会显著增加WSN的功耗。在此背景下,本文提出了一个将电池电量作为关键因素来评估WSN可靠性的模型。此外,该模型基于WSN所使用的路由算法。为了评估所提出的模型,考虑了三种场景来展示功耗对WSN可靠性的影响。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/54178aed2157/sensors-14-15760f20.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/d4b11068ffde/sensors-14-15760f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/ce107e4f7bd3/sensors-14-15760f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/d6d6add71fb1/sensors-14-15760f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/ec165a0cf28e/sensors-14-15760f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/24ea5958a3fb/sensors-14-15760f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/ba83018b9e20/sensors-14-15760f14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/fbee0a0d301a/sensors-14-15760f15.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/1fa33cd45b0e/sensors-14-15760f16.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/c603053093c1/sensors-14-15760f17.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/098a60d54470/sensors-14-15760f18.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/348ea5826ce7/sensors-14-15760f19.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/097c/4208144/54178aed2157/sensors-14-15760f20.jpg

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Sensors (Basel). 2012;12(1):806-38. doi: 10.3390/s120100806. Epub 2012 Jan 12.
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5
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