Lifetime Estimation of Wireless Body Area Sensor Networks Using Probabilistic Analysis

Abstract

A framework is proposed for estimating the lifetime of wireless body area sensor network (WBASN) using probabilistic analysis and Monte Carlo simulation. WBASN implements real-time health monitoring by outfitting patients with wireless, wearable vital sign sensors. In health monitoring, the loss of critical or emergency information is a serious issue so there is a need to ensure quality of service. It is important to have an estimate of the lifetime of the network in order to replace or recharge the batteries because the loss of critical data is not acceptable. The lifetime of the WBASN is defined as the duration of time until the first node fails due to battery depletion. Heart rate and blood glucose are monitored at a central location in a managed health care environment for this evaluation of WBASN performance. A parametric model of a health monitoring network (HMN) is created with sets of random input distributions. Probabilistic analysis is used to determine the timing and distribution of node failure in the HMN.