Title
Combinatorial analysis of body sensor networks subject to probabilistic competing failures
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.
Year
DOI
Venue
2015
10.1016/j.ress.2015.06.005
Reliability Engineering & System Safety
Keywords
Field
DocType
BDD,BSN,FCE,FDEP,FT,LF,PDEP,pdf,PF,PFDC,PFGE,SEA
Time domain,Combinatorial method,Monitoring system,Wearable computer,Engineering,Probabilistic logic,Combinatorial analysis,Wireless sensor network,Reliability engineering,Relay
Journal
Volume
ISSN
Citations 
142
0951-8320
11
PageRank 
References 
Authors
0.52
19
4
Name
Order
Citations
PageRank
Yujie Wang1131.89
Liudong Xing21214109.89
Honggang Wang31365124.06
Gregory Levitin41422115.34