Combinatorial analysis of body sensor networks subject to probabilistic competing failures

Body Sensor Networks (BSNs) have been developed to provide wearable, real-time health monitoring systems for many life-critical applications that require a high level of reliability. Therefore it is significant to analyze the reliability attribute of BSNs, contributing to their reliable designs and...

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Published inReliability engineering & system safety Vol. 142; pp. 388 - 398
Main Authors Wang, Yujie, Xing, Liudong, Wang, Honggang, Levitin, Gregory
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.10.2015
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ISSN0951-8320
1879-0836
DOI10.1016/j.ress.2015.06.005

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Abstract Body Sensor Networks (BSNs) have been developed to provide wearable, real-time health monitoring systems for many life-critical applications that require a high level of reliability. Therefore it is significant to analyze the reliability attribute of BSNs, contributing to their reliable designs and operations. This paper models reliability of BSNs subject to probabilistic competing failures. Specifically, in a BSN system, biomedical sensors sense physiological information that is then transmitted through a relay node to a sink device used by decision makers. When the relay fails, these sensors may be isolated in transmission with certain probabilities, depending on whether the remaining power can enable a long-range, direct transmission to the sink. This isolation effect prevents the system from being compromised by further failures of those sensors. However, biomedical sensors may experience propagated failures. If any of the propagated failures occurs before the relay failure, the entire system can fail. Therefore, there exists a competition in time domain between probabilistic failure isolation and propagation effects. This paper considers such probabilistic competing effects and different statistical relationships between local and propagated failures of sensors in reliability analysis of BSNs. A case study is given to illustrate application and advantages of the proposed combinatorial method. •Reliability of body sensor networks subject to probabilistic competing failures is modeled.•Different statistical relationships between local and propagated failures of biomedical sensors are considered.•A combinatorial method is suggested.
AbstractList Body Sensor Networks (BSNs) have been developed to provide wearable, real-time health monitoring systems for many life-critical applications that require a high level of reliability. Therefore it is significant to analyze the reliability attribute of BSNs, contributing to their reliable designs and operations. This paper models reliability of BSNs subject to probabilistic competing failures. Specifically, in a BSN system, biomedical sensors sense physiological information that is then transmitted through a relay node to a sink device used by decision makers. When the relay fails, these sensors may be isolated in transmission with certain probabilities, depending on whether the remaining power can enable a long-range, direct transmission to the sink. This isolation effect prevents the system from being compromised by further failures of those sensors. However, biomedical sensors may experience propagated failures. If any of the propagated failures occurs before the relay failure, the entire system can fail. Therefore, there exists a competition in time domain between probabilistic failure isolation and propagation effects. This paper considers such probabilistic competing effects and different statistical relationships between local and propagated failures of sensors in reliability analysis of BSNs. A case study is given to illustrate application and advantages of the proposed combinatorial method.
Body Sensor Networks (BSNs) have been developed to provide wearable, real-time health monitoring systems for many life-critical applications that require a high level of reliability. Therefore it is significant to analyze the reliability attribute of BSNs, contributing to their reliable designs and operations. This paper models reliability of BSNs subject to probabilistic competing failures. Specifically, in a BSN system, biomedical sensors sense physiological information that is then transmitted through a relay node to a sink device used by decision makers. When the relay fails, these sensors may be isolated in transmission with certain probabilities, depending on whether the remaining power can enable a long-range, direct transmission to the sink. This isolation effect prevents the system from being compromised by further failures of those sensors. However, biomedical sensors may experience propagated failures. If any of the propagated failures occurs before the relay failure, the entire system can fail. Therefore, there exists a competition in time domain between probabilistic failure isolation and propagation effects. This paper considers such probabilistic competing effects and different statistical relationships between local and propagated failures of sensors in reliability analysis of BSNs. A case study is given to illustrate application and advantages of the proposed combinatorial method. •Reliability of body sensor networks subject to probabilistic competing failures is modeled.•Different statistical relationships between local and propagated failures of biomedical sensors are considered.•A combinatorial method is suggested.
Author Xing, Liudong
Wang, Yujie
Levitin, Gregory
Wang, Honggang
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Keywords BDD
Body sensor network
Local failure
FCE
FDEP
Probabilistic functional dependence
FT
SEA
PFDC
PFGE
pdf
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Reliability analysis
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Probabilistic competing failure
Propagated failure with global effect
BSN
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Snippet Body Sensor Networks (BSNs) have been developed to provide wearable, real-time health monitoring systems for many life-critical applications that require a...
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SubjectTerms Body sensor network
Combinatorial analysis
Devices
Failure
Local failure
Networks
Probabilistic competing failure
Probabilistic functional dependence
Probabilistic methods
Probability theory
Propagated failure with global effect
Relay
Reliability analysis
Sensors
Title Combinatorial analysis of body sensor networks subject to probabilistic competing failures
URI https://dx.doi.org/10.1016/j.ress.2015.06.005
https://www.proquest.com/docview/1732832195
https://www.proquest.com/docview/1753487716
Volume 142
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