A Model for Obstacles to be used in Simulations of Wireless Sensor Networks and its Application in studying Routing Protocol Performance

  • Authors:

  • Ioannis Chatzigiannakis;Georgios Mylonas;Sotiris Nikoletseas

  • Affiliations:

  • Department of Computer Engineering and Informatics,and Computer Technology Institute (CTI) University of Patras 26500 PatrasGreece;Department of Computer Engineering and Informatics,and Computer Technology Institute (CTI) University of Patras 26500 PatrasGreece;Department of Computer Engineering and Informatics,and Computer Technology Institute (CTI) University of Patras 26500 PatrasGreece

  • Venue:
  • Simulation
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a simple obstacle model to be used while simulating wireless sensor networks. To the best of our knowledge, this is the first time such an integrated and systematic obstacle model for these networks has been proposed. We define several types of obstacles that can be found inside the deployment area of a wireless sensor network and provide a categorization of these obstacles based on their nature (physical and communication obstacles, i.e. obstacles that are formed out of node distribution patterns or have physical presence, respectively), their shape and their change of nature over time. We make an eXtension to a custom-made sensor network simulator (simDust) and conduct a number of simulations in order to study the effect of obstacles on the performance of some representative (in terms of their logic) data propagation protocols for wireless sensor networks. Our findings confirm that obstacle presence has a significant impact on protocol performance, and also that different obstacle shapes and sizes may affect each protocol in different ways. This provides an insight into how a routing protocol will perform in the presence of obstacles and highlights possible protocol shortcomings. Moreover, our results show that the effect of obstacles is not directly related to the density of a sensor network, and cannot be emulated only by changing the network density.