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用于监测湿度和潮湿环境的可靠无线传感器网络。

Trustworthy Wireless Sensor Networks for Monitoring Humidity and Moisture Environments.

机构信息

Centre for Applied Mathematics and Electronics, Serbian Armed Forces, 11000 Belgrade, Serbia.

Faculty of Technical Sciences, University of Novi Sad, 21000 Novi Sad, Serbia.

出版信息

Sensors (Basel). 2021 May 24;21(11):3636. doi: 10.3390/s21113636.

DOI:10.3390/s21113636
PMID:34073687
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8197129/
Abstract

Wireless sensors networks (WSNs) are characterized by flexibility and scalability in any environment. These networks are increasingly used in agricultural and industrial environments and have a dual role in data collection from sensors and transmission to a monitoring system, as well as enabling the management of the monitored environment. Environment management depends on trust in the data collected from the surrounding environment, including the time of data creation. This paper proposes a trust model for monitoring humidity and moisture in agricultural and industrial environments. The proposed model uses a digital signature and public key infrastructure (PKI) to establish trust in the data source, i.e., the trust in the sensor. Trust in data generation is essential for real-time environmental monitoring and subsequent analyzes, thus timestamp technology is implemented here to further ensure that gathered data are not created or changed after the assigned time. Model validation is performed using the Castalia network simulator by testing energy consumption at the receiver and sender nodes and the delay incurred by creating or validating a trust token. In addition, validation is also performed using the Ascertia TSA Crusher application for the time consumed to obtain a timestamp from the free TSA. The results show that by applying different digital signs and timestamps, the trust entity of the WSN improved significantly with an increase in power consumption of the sender node by up to 9.3% and receiver node by up to 126.3% for a higher number of nodes, along with a packet delay of up to 15.6% and an average total time consumed up to 1.186 s to obtain the timestamp from the best chosen TSA, which was as expected.

摘要

无线传感器网络 (WSN) 在任何环境中都具有灵活性和可扩展性。这些网络越来越多地应用于农业和工业环境中,它们在从传感器收集数据并传输到监控系统以及实现对监控环境的管理方面具有双重作用。环境管理依赖于对从周围环境收集的数据的信任,包括数据创建的时间。本文提出了一种用于监测农业和工业环境中湿度和水分的信任模型。所提出的模型使用数字签名和公钥基础设施 (PKI) 来建立对数据源(即传感器)的信任。对数据生成的信任对于实时环境监测和后续分析至关重要,因此这里实现了时间戳技术,以进一步确保所收集的数据在指定时间后不会被创建或更改。通过使用 Castalia 网络模拟器对接收方和发送方节点的能量消耗以及创建或验证信任令牌所产生的延迟进行测试,对模型进行了验证。此外,还使用 Ascertia TSA Crusher 应用程序对从免费 TSA 获取时间戳所消耗的时间进行了验证。结果表明,通过应用不同的数字签名和时间戳,WSN 的信任实体得到了显著改善,发送方节点的功耗增加了 9.3%,接收方节点的功耗增加了 126.3%,节点数量增加了,数据包延迟增加了 15.6%,从最佳选择的 TSA 获得时间戳的平均总时间消耗增加到 1.186 秒,这是预期的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/1528fd530bd4/sensors-21-03636-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/ccd0638e8c34/sensors-21-03636-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/b5b015740a48/sensors-21-03636-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/7ce5ef13d7f6/sensors-21-03636-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/1ea25da061e7/sensors-21-03636-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/dab6313d428e/sensors-21-03636-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/9b7a1d899793/sensors-21-03636-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/40f21fdf9026/sensors-21-03636-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/cef8ee8598cb/sensors-21-03636-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/1528fd530bd4/sensors-21-03636-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/ccd0638e8c34/sensors-21-03636-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/b5b015740a48/sensors-21-03636-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/7ce5ef13d7f6/sensors-21-03636-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/1ea25da061e7/sensors-21-03636-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/dab6313d428e/sensors-21-03636-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/9b7a1d899793/sensors-21-03636-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/40f21fdf9026/sensors-21-03636-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/cef8ee8598cb/sensors-21-03636-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89cf/8197129/1528fd530bd4/sensors-21-03636-g009.jpg

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