Assessment of reliability and availability of wireless sensor networks in industrial applications by considering permanent faults

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Concurrency and Computation-Practice & Experience Pub Date : 2024-10-04 DOI:10.1002/cpe.8252
Arash Heidari, Zahra Amiri, Mohammad Ali Jabraeil Jamali, Nima Jafari
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Abstract

Wireless Sensor Networks (WSNs) are critical for communication within a mile radius and industrial applications. These networks are very prone to failure due to their enormous number of nodes and their unique hardware and software restrictions. To make sure network performance, a lot of study needs to be done to improve failure tolerance and stability. This study looks at how to judge the availability and dependability of WSNs that have long-term issues. The suggested method checks how well a network works in various failure cases by using fault trees and Markov chain analysis. Such methods help us find and study possible failure scenarios and how they might impact the network's dependability in a planned way. The results show that WSNs have major flaws and give useful suggestions for making the systems work better. The findings show that using these evaluation methods may greatly enhance the ability to handle faults, lower the risk of damage, and allow developers of WSNs to make smart choices.

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通过考虑永久性故障评估工业应用中无线传感器网络的可靠性和可用性
无线传感器网络(WSN)对于方圆一英里内的通信和工业应用至关重要。这些网络由于节点数量庞大、硬件和软件限制独特,很容易出现故障。为确保网络性能,需要进行大量研究,以提高故障容限和稳定性。本研究探讨了如何判断存在长期问题的 WSN 的可用性和可靠性。所建议的方法通过使用故障树和马尔可夫链分析来检查网络在各种故障情况下的工作情况。这些方法可以帮助我们找到并研究可能出现的故障情况,以及这些情况会如何有计划地影响网络的可靠性。结果表明,WSN 存在重大缺陷,并为使系统更好地运行提出了有用的建议。研究结果表明,使用这些评估方法可以大大提高处理故障的能力,降低损坏的风险,并让 WSN 的开发人员做出明智的选择。
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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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