Cover Image

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Dezfouli, Behnam, Radi, Marjan, Whitehouse, Kamin, Abd. Razak, Shukor, Tan, Hwee Pink
Format: Article
Published: Association for Computing Machinery 2014
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/52048/
http://dx.doi.org/10.1145/2629352
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.52048
record_format eprints
spelling my.utm.520482018-11-30T07:00:28Z http://eprints.utm.my/id/eprint/52048/ CAMA: efficient modeling of the capture effect for low-power wireless networks Dezfouli, Behnam Radi, Marjan Whitehouse, Kamin Abd. Razak, Shukor Tan, Hwee Pink QA75 Electronic computers. Computer science 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. Association for Computing Machinery 2014 Article PeerReviewed Dezfouli, Behnam and Radi, Marjan and Whitehouse, Kamin and Abd. Razak, Shukor and Tan, Hwee Pink (2014) CAMA: efficient modeling of the capture effect for low-power wireless networks. ACM Transactions on Sensor Networks, 11 (1). ISSN 1550-4859 http://dx.doi.org/10.1145/2629352 DOI: 10.1145/2629352
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Dezfouli, Behnam
Radi, Marjan
Whitehouse, Kamin
Abd. Razak, Shukor
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 Article
author Dezfouli, Behnam
Radi, Marjan
Whitehouse, Kamin
Abd. Razak, Shukor
Tan, Hwee Pink
author_facet Dezfouli, Behnam
Radi, Marjan
Whitehouse, Kamin
Abd. Razak, Shukor
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 Association for Computing Machinery
publishDate 2014
url http://eprints.utm.my/id/eprint/52048/
http://dx.doi.org/10.1145/2629352
_version_ 1643653137600348160
score 13.211869

Similar Items