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

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 effec...

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Main Authors: DEZFOULI, Behnam, RADI, Marjan, WHITEHOUSE, Kamin, RAZAK, Shukor Abd, TAN, Hwee-Pink
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/sis_research/2964
https://ink.library.smu.edu.sg/context/sis_research/article/3964/viewcontent/ACMSN2014.pdf
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spelling sg-smu-ink.sis_research-39642016-01-28T07:56:22Z CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks DEZFOULI, Behnam RADI, Marjan WHITEHOUSE, Kamin RAZAK, Shukor Abd TAN, Hwee-Pink 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. 2014-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2964 info:doi/10.1145/2629352 https://ink.library.smu.edu.sg/context/sis_research/article/3964/viewcontent/ACMSN2014.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Wireless sensor networks radio interference packet collisions Computer and Systems Architecture Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Wireless sensor networks
radio interference
packet collisions
Computer and Systems Architecture
Software Engineering
spellingShingle Wireless sensor networks
radio interference
packet collisions
Computer and Systems Architecture
Software Engineering
DEZFOULI, Behnam
RADI, Marjan
WHITEHOUSE, Kamin
RAZAK, Shukor Abd
TAN, Hwee-Pink
CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks
description 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.
format text
author DEZFOULI, Behnam
RADI, Marjan
WHITEHOUSE, Kamin
RAZAK, Shukor Abd
TAN, Hwee-Pink
author_facet DEZFOULI, Behnam
RADI, Marjan
WHITEHOUSE, Kamin
RAZAK, Shukor Abd
TAN, Hwee-Pink
author_sort DEZFOULI, Behnam
title CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks
title_short CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks
title_full CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks
title_fullStr CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks
title_full_unstemmed CAMA: Efficient Modeling of the Capture Effect for Low Power Wireless Networks
title_sort cama: efficient modeling of the capture effect for low power wireless networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/sis_research/2964
https://ink.library.smu.edu.sg/context/sis_research/article/3964/viewcontent/ACMSN2014.pdf
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