research-article

CAMA: Efficient Modeling of the Capture Effect for Low-Power Wireless Networks

Authors:

Behnam Dezfouli,

Kamin Whitehouse,

Shukor Abd Razak,

Hwee-Pink TanAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 11, Issue 1

Article No.: 20, Pages 1 - 43

https://doi.org/10.1145/2629352

Published: 26 August 2014 Publication History

Abstract

Network simulation is an essential tool for the design and evaluation of wireless network protocols, and realistic channel modeling is essential for meaningful analysis. Recently, several network protocols have demonstrated substantial network performance improvements by exploiting the capture effect, but existing models of the capture effect are still not adequate for protocol simulation and analysis. Physical-level models that calculate the signal-to-interference-plus-noise ratio (SINR) for every incoming bit are too slow to be used for large-scale or long-term networking experiments, and link-level models such as those currently used by the NS2 simulator do not accurately predict protocol performance. In this article, we propose a new technique called the capture modeling algorithm (CAMA) that provides the simulation fidelity of physical-level models while achieving the simulation time of link-level models. We confirm the validity of CAMA through comparison with the empirical traces of the experiments conducted by various numbers of CC1000 and CC2420-based nodes in different scenarios. Our results indicate that CAMA can accurately predict the packet reception, corruption, and collision detection rates of real radios, while existing models currently used by the NS2 simulator produce substantial prediction error.

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CAMA: Efficient Modeling of the Capture Effect for Low-Power Wireless Networks

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 11, Issue 1

November 2014

631 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/2648771

Editor:
Chenyang Lu
Department of Computer Science and Engineering / School of Engineering and Applied Sciences / Washington University / 1 Brookings Drive / St. Louis, MO 63130

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Copyright © 2014 ACM.

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Association for Computing Machinery

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 26 August 2014

Accepted: 01 May 2014

Revised: 01 January 2014

Received: 01 April 2013

Published in TOSN Volume 11, Issue 1

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https://doi.org/10.1109/TMC.2021.3138495
Mehjabin STekeoglu AYounis MEbrahimabadi MChandran RSookoor TKarimi N(2023)A Networked System Dependability Validation Framework Using Physical and Virtual NodesIEEE Access10.1109/ACCESS.2023.333068811(127242-127254)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3330688
Li CRamanna VWebber DHunter CHack TDezfouli B(2022)Sensifi: A Wireless Sensing System for Ultrahigh-Rate ApplicationsIEEE Internet of Things Journal10.1109/JIOT.2021.30891599:3(2025-2043)Online publication date: 1-Feb-2022
https://doi.org/10.1109/JIOT.2021.3089159
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