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 in | Reliability engineering & system safety Vol. 142; pp. 388 - 398 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.10.2015
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Online Access | Get full text |
ISSN | 0951-8320 1879-0836 |
DOI | 10.1016/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. |
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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 |
Author_xml | – sequence: 1 givenname: Yujie surname: Wang fullname: Wang, Yujie email: ywang2@umassd.edu organization: University of Massachusetts, Dartmouth, MA 02747, USA – sequence: 2 givenname: Liudong orcidid: 0000-0003-1606-1644 surname: Xing fullname: Xing, Liudong email: lxing@umassd.edu organization: University of Massachusetts, Dartmouth, MA 02747, USA – sequence: 3 givenname: Honggang surname: Wang fullname: Wang, Honggang email: hwang1@umassd.edu organization: University of Massachusetts, Dartmouth, MA 02747, USA – sequence: 4 givenname: Gregory surname: Levitin fullname: Levitin, Gregory email: levitin@iec.co.il organization: The Israel Electric Corporation, PO Box 10, Haifa 31000, Israel |
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Keywords | BDD Body sensor network Local failure FCE FDEP Probabilistic functional dependence FT SEA PFDC PFGE PF Reliability analysis LF PDEP 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 |
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