Wireless sensor node deployment strategy for hilly terrains - a surface approximation based approach

Sensor deployment in a wireless sensor network (WSN) is a challenging task due to the high chance of occurrence of the error in the deployment process, which makes the network inefficient. Particularly in three-dimensional (3D) WSN, the ideal positioning of sensor nodes over the ground with precise coverage and connectivity is a very significant consideration in the deployment of sensors. Various models for 2D sensor deployment have been proposed to date, but in real-world scenarios, the target field (field of interest) is not always 2D flat surface and therefore a 2D deployment model cannot address the issue of deploying sensor nodes on uneven surfaces such as hilly terrains. In this paper, we presented a surface approximation-based sensor deployment using truncated octahedron (SASD-TO) to solve the problems of sensor deployment on an irregular surface. Using the B-Spline, a 3D model of the target surface is approximated and then a Truncated Octahedron is used to estimate the exact coordinates of a sensor node. A very decent coverage area as high as 98% on average, whereas at lowest 2% of the uncovered area and 8% of the superimposed area were observed.

• Publication year

  2019

• Venue

  IET Wireless Sensor Systems

• Publication date

  2019-05-15

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1049/IET-WSS.2018.5095
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Design and deployment of a smart system for data gathering in aquaculture tanks using wireless sensor networks

  2017cited by this paper
• B-Spline Surface Fitting on Scattered Points

  2016cited by this paper
• Coverage and connectivity in three-dimensional networks with random node deployment

  2015cited by this paper
• Method for Optimal Sensor Deployment on 3D Terrains Utilizing a Steady State Genetic Algorithm with a Guided Walk Mutation Operator Based on the Wavelet Transform

  2012cited by this paper
• Topology Construction of 3D Wireless Sensor Network

  2012cited by this paper
• Hexagonal grid-based sensor deployment algorithm

  2010cited by this paper
• Practical Deployments of Wireless Sensor Networks: a Survey

  2010cited by this paper
• Optimal Patterns for Four-Connectivity and Full Coverage in Wireless Sensor Networks

  2010cited by this paper
• Critical Density for Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks Using Continuum Percolation

  2009cited by this paper
• A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification

  2009cited by this paper
• Coverage Strategies in Wireless Sensor Networks

  2006cited by this paper
• Integrated coverage and connectivity configuration for energy conservation in sensor networks

  2005cited by this paper
• Maintaining Sensing Coverage and Connectivity in Large Sensor Networks

  2005cited by this paper
• Underwater acoustic sensor networks: research challenges

  2005cited by this paper
• SUPERCONVERGENCE PHENOMENA ON THREE-DIMENSIONAL MESHES

  2005cited by this paper
• Extremal properties of three-dimensional sensor networks with applications

  2004cited by this paper
• Variable radii connected sensor cover in sensor networks

  2004cited by this paper
• Sensor deployment strategy for target detection

  2002cited by this paper
• Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks

  2002cited by this paper
• A coverage-preserving node scheduling scheme for large wireless sensor networks

  2002cited by this paper
• A basis for 3-D cellular networks

  2001cited by this paper

• A Survey of Three-Dimensional Wireless Sensor Networks Deployment Techniques

  2025cites this paper
• Solving Target Coverage Problem in Wireless Sensor Networks using Greedy Approach

  2020cites this paper
• Sensor Coverage Strategy in Underwater Wireless Sensor Networks

  2020cites this paper