Abstract

Abstract Many literature papers evaluate solutions in wireless sensor networks by simulation experiments. However, little attention is given to the adequacy of the simulator propagation models to the environment in which such solutions are employed. This can lead to imprecise or inconsistent results in relation to the real world. This paper presents a methodology for adjusting the parameters of these models. In particular, we present experimental results for rainforest environments, which can be the goal of many sensor networks monitoring applications. The impact of the proposed approach is shown by evaluating a localization solution. The results show that this procedure is necessary for a higher fidelity of simulation experiments.

Highlights

  • Many research efforts are being dedicated to the wireless sensor networks (WSNs) [3] in the last few years

  • We investigate the impact of the incorrect tuning of propagation parameters in the NS-2 simulator for actual applications

  • The communication becomes unstable due to the low signalto-noise ratio (SNR) and presence of obstacles in such a configuration that contributes to the signal instead of degrading it

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Summary

Introduction

Many research efforts are being dedicated to the wireless sensor networks (WSNs) [3] in the last few years. In the initial phase of the WSN’s development many solutions were proposed under conceptual aspects with strong use of experimentation by simulation These are solutions such as protocols and algorithms for MAC [30], routing [4], localization [9], and many others which depends on the wireless communication and the channel characteristics. At first we did practical experiments to measure the received power, the link quality and delivery ratio by using two popular platforms for WSN in the Amazon rainforest. This is an important contribution itself, once we do not have similar results in the literature.

Propagation models
Free Space propagation model
Shadowing propagation model
Related work
Rainforest scenario characterization
Test scenario
Wireless sensor network platforms
Test procedure
Experimental results
Shadowing model parameters estimation
Tuning propagation model parameters
Localization experiments
Conclusion
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