Energy Efficiency in Two-Tiered Wireless Sensor Networks

TL;DR

This paper investigates optimal deployment strategies for two-tiered wireless sensor networks to minimize power consumption, providing analytical solutions for specific cases and proposing Lloyd algorithms for general scenarios, with significant power savings demonstrated.

Contribution

It introduces analytical solutions for optimal node placement in specific scenarios and develops Lloyd algorithms for general deployment optimization in two-tiered WSNs.

Findings

Optimal AP deployment is a linear transformation of the quantizer for density f.

The single BS should be at the geometric centroid of the sensing field.

Proposed algorithms can reduce power consumption by up to 79% compared to random deployment.

Abstract

We study a two-tiered wireless sensor network (WSN) consisting of $N$ access points (APs) and $M$ base stations (BSs). The sensing data, which is distributed on the sensing field according to a density function $f$, is first transmitted to the APs and then forwarded to the BSs. Our goal is to find an optimal deployment of APs and BSs to minimize the average weighted total, or Lagrangian, of sensor and AP powers. For $M=1$, we show that the optimal deployment of APs is simply a linear transformation of the optimal $N$-level quantizer for density $f$, and the sole BS should be located at the geometric centroid of the sensing field. Also, for a one-dimensional network and uniform $f$, we determine the optimal deployment of APs and BSs for any $N$ and $M$. Moreover, to numerically optimize node deployment for general scenarios, we propose one- and two-tiered Lloyd algorithms and analyze their convergence properties. Simulation results show that, when compared to random deployment, our algorithms can save up to 79\% of the power on average.