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Investigating a physically-based signal power model for robust low power wireless link simulation
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International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems table of contents
Vancouver, British Columbia, Canada
SESSION: Simulation table of contents
Pages 37-46  
Year of Publication: 2008
ISBN:978-1-60558-235-1
Authors
Tal Rusak  Cornell University, Ithaca, NY, USA
Philip A. Levis  Stanford University, Stanford, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
ACM  New York, NY, USA
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ABSTRACT

We propose deriving wireless simulation models from experimental traces of radio signal strength. Because experimental traces have holes due to packet losses, we explore two algorithms for filling the gaps in lossy experimental traces. Using completed traces, we apply the closest-fit pattern matching (CPM) algorithm, originally designed for modeling external interference, to model signal strength.

We compare the observed link behavior using our models with that of the experimental packet trace. Our approach results in more accurate packet reception ratios than current simulation methods, reducing the absolute error in PRR by up to about 30%. We also find that using CPM for signal strength improves simulation of packet burstiness, reducing the Kantorovich-Wasserstein (KW) distance of conditional packet delivery functions (CPDFs) by a factor of about 3 for intermediate links.

These improvements give TOSSIM, a standard sensor network simulator, a better capability to capture real-world dynamics and edge conditions that protocol designers typically must wait until deployment to detect.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Wireless Valley Software, http://www.connect802.com/w-valley.htm, 2003-2005.
 
2
CC2420 Datasheet, Texas Instruments Inc., http://focus.ti.com/docs/prod/folders/print/cc2420.html, 2007.
 
3
TinyOS repository (http://www.tinyos.net/), /tinyos-2.x-contrib/stanford-sing/apps/RssiSample, 2007.
 
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Mentum Inc., http://www.mentum.com/, 2008.
 
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S. Bae and K. Kim. Analysis of Wireless Link for Mobile Sensor Network. In Proceedings of ICEE'06, 2006.
 
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P. Levis, D. Gay, V. Handziski, J. Hauer, B. Greenstein, M. Turon, J. Hui, K. Klues, C. Sharp, R. Szewczyk, et al. T2: A second generation OS for embedded sensor networks. Technical report, TKN-05-007, Telecommunication Networks Group, Technische Universitat Berlin, 2005.
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P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, et al. TinyOS: An Operating System for Sensor Networks. Ambient Intelligence, 2005.
 
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C. Metcalf. TOSSIM Live: Towards a Testbed in a Thread. Master's Thesis, 2007.
 
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M. Zuniga and B. Krishnamachari. Analyzing the transitional region in low power wireless links. In SECON'04: Proceedings of the Conference on sensor and ad hoc communications and networks, 2004, pages 517--526, 2004.


Collaborative Colleagues:
Tal Rusak: colleagues
Philip A. Levis: colleagues