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Copula-based reliability modelling of wireless sensor networks with dependent failures
Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för industriell ekonomi, industridesign och maskinteknik, Industriell ekonomi. Högskolan i Gävle, Centrum för logistik och innovativ produktion.
School of Data Science, Department of Data Science, Guizhou Institute of Technology, Guiyang, 550003, Chin.
Department of Mathematics, Reliability Center of Guizhou Province, Guizhou University, Guiyang, 550025, China.
Department of Mathematics, Reliability Center of Guizhou Province, Guizhou University, Guiyang, 550025, China.
2019 (Engelska)Ingår i: International Journal of Sensor Networks (IJSNet), ISSN 1748-1279, E-ISSN 1748-1287, Vol. 31, nr 2, s. 90-98Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Wireless sensor networks (WSNs) have widely been applied in various industries and business fields covering large geographical regions. It is therefore important to be able to model, assess and predict the reliability of WSNs since the failures can have a great effect on the monitoring or control systems that are normally depending on the WSNs. In this paper, the general WSN reliability models are developed by deleting the independent assumption of component or subsystem failures and are consequently more reasonable to characterise the failure process of WSNs. The methodology in the proposed WSN reliability models is to consider that the failure times of subsystems are dependent variables and their joint distribution is obtained by binding their marginal failure distributions together through a copula function. For specific Frank copula functions, the Star-based WSN reliability models are derived and their properties are also discussed in this paper. 

Ort, förlag, år, upplaga, sidor
InderScience Publishers, 2019. Vol. 31, nr 2, s. 90-98
Nyckelord [en]
Control system, Copula function, Dependence, Failure time, Joint distribution, Reliability model, Star-based WSN, Subsystem, Wireless sensor network, WSN
Nationell ämneskategori
Annan data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:hig:diva-30739DOI: 10.1504/IJSNET.2019.102185ISI: 000485658600003Scopus ID: 2-s2.0-85072250185OAI: oai:DiVA.org:hig-30739DiVA, id: diva2:1358285
Tillgänglig från: 2019-10-07 Skapad: 2019-10-07 Senast uppdaterad: 2019-10-11Bibliografiskt granskad

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