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A Graph-based Strategic Sensor Deployment Approach for k-coverage in WSN

Lakshmikanta Sau, Priyadarshi Mukherjee, Sasthi C. Ghosh

TL;DR

A new sensor deployment approach is proposed here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes.

Abstract

This paper studies a graph-based sensor deployment approach in wireless sensor networks (WSNs). Specifically, in today's world, where sensors are everywhere, detecting various attributes like temperature and movement, their deteriorating lifetime is indeed a very concerning issue. In many scenarios, these sensors are placed in extremely remote areas, where maintenance becomes challenging. As a result, it is not very wise to depend on a single sensor to obtain data from a particular terrain or place. Hence, multiple sensors are deployed in these places, such that no problem arises if one or few of them fail. In this work, this problem of intelligent placement of sensors is modelled from the graph theoretic point of view. We propose a new sensor deployment approach here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes. Finally, the numerical results also support our claims and provide insights regarding the selection of parameters that enhance the system performance.

A Graph-based Strategic Sensor Deployment Approach for k-coverage in WSN

TL;DR

A new sensor deployment approach is proposed here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes.

Abstract

This paper studies a graph-based sensor deployment approach in wireless sensor networks (WSNs). Specifically, in today's world, where sensors are everywhere, detecting various attributes like temperature and movement, their deteriorating lifetime is indeed a very concerning issue. In many scenarios, these sensors are placed in extremely remote areas, where maintenance becomes challenging. As a result, it is not very wise to depend on a single sensor to obtain data from a particular terrain or place. Hence, multiple sensors are deployed in these places, such that no problem arises if one or few of them fail. In this work, this problem of intelligent placement of sensors is modelled from the graph theoretic point of view. We propose a new sensor deployment approach here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes. Finally, the numerical results also support our claims and provide insights regarding the selection of parameters that enhance the system performance.

Paper Structure

This paper contains 11 sections, 3 theorems, 18 equations, 8 figures.

Table of Contents

  1. Introduction
  2. System Model and Preliminaries
  3. Definitions
  4. Network Model
  5. Proposed Strategy
  6. Sensor Deployment Strategy
  7. Required Number of Sensors for $k$-coverage
  8. Sensor Density per Unit Area
  9. Required Number of Sensor for a Plane
  10. Numerical Results
  11. Conclusion

Key Result

Lemma 1

A hexagon $H_{r}$ of side $r$ can contain a maximum of three non-overlapping hexagons $H_{r/2}$, each of side $r/2$.

Figures (8)

  • Figure 1: Two different tilling of Euclidean plane.
  • Figure 2: Different shape tiles
  • Figure 3: Sensor Deployment Strategy
  • Figure 4: Impact of sensing radius on sensor density.
  • Figure 5: Impact of $k$-coverage on sensor density.
  • ...and 3 more figures

Theorems & Definitions (14)

  • Definition 1
  • Definition 2
  • Definition 3
  • Definition 4
  • Definition 5
  • Definition 6
  • Definition 7
  • Definition 8
  • Lemma 1
  • proof
  • ...and 4 more