On Periodic Node Deployment in Wireless Sensor Networks: A Statistical Analysis

TL;DR

This paper presents a stochastic model for periodic sensor deployment in wireless sensor networks, analyzing node stability and optimizing deployment timing and quantity to ensure minimal connectivity with limited battery life.

Contribution

It introduces a discrete birth-continuous death process model for bursty node deployment and derives optimal deployment parameters for network stability.

Findings

Mean and variance of node count converge to finite steady states

Optimal deployment time and number of redeployments minimize costs

System stability is guaranteed through convergence analysis

Abstract

Rapid progress made in the field of sensor technology, wireless communication, and computer networks in recent past, led to the development of wireless Ad-hoc sensor networks, consisting of small, low-cost sensors, which can monitor wide and remote areas with precision and liveliness unseen to the date without the intervention of a human operator. This work comes up with a stochastic model for periodic sensor-deployment (in face of their limited amount of battery-life) to maintain a minimal node-connectivity in wireless sensor networks. The node deployment cannot be modeled by using results from conventional continuous birth-death process, since new nodes are added to the network in bursts, i.e. the birth process is not continuous in practical situations. We analyze the periodic node deployment process using discrete birth-continuous death process and obtain two important statistical measures of the existing number of nodes in the network, namely the mean and variance. We show that the above mentioned sequences of mean and variances always converge to finite steady state values, thus ensuring the stability of the system. We also develop a cost function for the process of periodic deployment of sensor nodes and minimize it to find the optimal time ({\tau}) and optimum number of re-deployment (q) for maintaining minimum connectivity in the network.