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Performance Evaluation
Volume 64, Issues 7-8, August 2007, Pages 715-736
 
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doi:10.1016/j.peva.2006.11.003    
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Copyright © 2006 Elsevier Ltd All rights reserved.

Fluid models for large-scale wireless sensor networks

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C.-F. Chiasserinia, R. Gaetab, Corresponding Author Contact Information, E-mail The Corresponding Author, M. Garettob, M. Gribaudob, D. Maninib and M. Serenob

aDipartimento di Elettronica, Politecnico di Torino, Italy

bDipartimento di Informatica, Università di Torino, Italy


Received 3 August 2005; 
revised 5 May 2006. 
Available online 30 December 2006.

Abstract

We develop an analytical framework for the study of large-scale, wireless sensor networks. We use a fluid approach, i.e., we represent the sensor network by a continuous fluid entity distributed on the network area. We assume that sensors employ a CSMA/CA mechanism to access the channel and a minimum energy consumption criterion to select traffic routes, and accurately model these aspects. Furthermore, the framework accounts for energy consumption and is able to model the active/sleep dynamics of the nodes. We validate our approach through simulation and show that the proposed framework is well suited for describing the properties of large sensor networks and understanding their complex behavior. To the best of our knowledge, our framework is one of few analytical models developed for large-scale sensor networks which can accurately capture the main aspects of these systems.

Keywords: Wireless sensor networks; Power-aware/limited systems; Fluid models; Wireless systems performance

Article Outline

1. Introduction
2. Related work
3. The fluid framework
4. Sensor network scenario
5. The sensor network model
5.1. A minimum-energy routing strategy: Computing View the MathML source
5.1.1. Computing View the MathML source
5.1.2. Computing View the MathML source
5.1.3. Computing View the MathML source
5.1.4. Computing View the MathML source
5.1.5. Computing View the MathML source
5.2. Channel contention and data transmission: Computing View the MathML source and View the MathML source
5.3. Mean packet delivery delay: Computing View the MathML source
5.3.1. Computing View the MathML source for always active sensors
5.3.2. Computing View the MathML source for active and sleeping sensors
6. Results
6.1. Model validation
6.2. Model exploitation
6.3. Model solution complexity and accuracy
7. Conclusions
Acknowledgements
Appendix A. Appendix
A.1. Computation of the minimum-energy path (Eq. (9))
A.2. Computation of the mean number of transmissions freezing the backoff counter
References
Vitae













Corresponding Author Contact InformationCorresponding address: University of Turin, Department of Computer Science, Corso Svizzera 185, 10149 Turin, Italy. Tel.: +39 011 670 67 70; fax: +39 011 75 16 03.

Performance Evaluation
Volume 64, Issues 7-8, August 2007, Pages 715-736
 
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