A Source Coding Perspective on Node Deployment in Two-Tier Networks

Abstract

Abstract-Multi-tier networks have many applications in different fields. We define a novel two-tier quantizer that can be applied to different node deployment problems including the energy conservation in two-tier wireless sensor networks (WSNs) consisting of N access points (APs) and M fusion centers (FCs). We aim at finding an optimal deployment of APs and FCs to minimize the average weighted total, or Lagrangian, of sensor and AP powers. For one fusion center, 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 FC should be located at the geometric centroid of the sensing field. We also provide the exact expression of the AP-Sensor power function and prove its convexity. For more than one fusion center, M > 1, we provide a necessary condition for the optimal deployment. Furthermore, to numerically optimize the AP and FC deployment, we propose three Lloyd-like algorithms and analyze their convergence. Simulation results show that our algorithms outperform the existing algorithms.

Using Quantization to Deploy Heterogeneous Nodes in Two-Tier Wireless Sensor Networks

“…We provide the experimental results in two heterogeneous two-tier WSNs: (i) WSN1: A heterogeneous WSN including 1 FC and 20 APs; (ii) WSN2: A heterogeneous WSN including 4 FCs and 20 APs. We consider the same target domain Ω as in [1], [6], i.e., Ω = [0, 10] 2 . The data rate density function is set to a uniform function, f (ω) = 1 Ω dA = 0.01.…”

“…MER is a combination of Multiplicatively weighted Voronoi Partition [20] and Bellman-Ford algorithms [21,Section 2.3.4]. More details about MER, AC, and DC can be found in [1]. Figs.…”

“…In this paper, we study the node deployment problem in heterogeneous two-tier WSNs consisting of heterogeneous APs and heterogeneous FCs, with distortion defined as the total wireless communication power consumption. The optimal energy-efficient sensor deployment in homogeneous WSNs is studied in [1]. However, the homogeneous two-tier WSNs in [1] do not address various challenges that exist in the heterogeneous two-tier WSNs, e.g., unlike regular Voronoi diagrams for homogeneous WSNs, the optimal cells in heterogeneous WSNs may be non-convex, not star-shaped or even disconnected, and the cell boundaries may not be hyperplanes.…”

A Generalization of Principal Component Analysis

“…Dimension reduction is achieved by considering only the first few principal vectors and the corresponding components [4]. PCA can be utilized in a variety of applications including novelty detection [5], data clustering [6]- [9], and outlier detection [10], [11].…”

Movement-Efficient Sensor Deployment in Wireless Sensor Networks With Limited Communication Range

“…A common communication model [3], [13]- [15] assumes that each sensor node is able to communicate with sensors in a limited communication range R c . Energy efficiency is another key issue in MWSNs, as most sensors have limited battery energy, and it is inconvenient or even infeasible to replenish the batteries of numerous densely deployed sensors [21]. In general, the energy consumption of a device includes communication energy, data processing energy [22], sensing energy, and movement energy.…”