Reliability analysis of body sensor networks with correlated isolation groups

Area of Science:

• Biomedical Engineering
• Network Reliability
• Wireless Sensor Networks

Background:

• Body Sensor Networks (BSNs) are vital for healthcare, especially during pandemics like COVID-19.
• Existing reliability models often overlook complex failure dependencies and random behaviors in BSNs.

Purpose of the Study:

• To develop a methodology for modeling and analyzing BSN reliability.
• To incorporate correlated functional dependence (FDEP) and random isolation time into BSN reliability analysis.
• To address the complexities introduced by correlations and time-domain competition in BSN failures.

Main Methods:

• A combinatorial and analytical methodology is proposed to model BSN reliability.
• The methodology accounts for FDEP where biosensors rely on a central relay.
• The approach considers random isolation times and correlations among biosensors and relays.

Main Results:

• The proposed method effectively models BSN reliability under correlated functional dependence and random isolation.
• Analysis revealed complexities arising from shared relays and alternative communication paths.
• The methodology was demonstrated via a case study and validated using continuous-time Markov chain analysis.

Conclusions:

• The developed methodology provides a robust framework for BSN reliability analysis.
• Understanding FDEP and isolation times is crucial for BSN performance optimization.
• This work enhances the design and deployment of reliable BSNs for critical applications.