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Experimentation and performance evaluation of rate adaptation algorithms in wireless mesh networks
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International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive
Proceedings of the 5th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks table of contents
Vancouver, British Columbia, Canada
SESSION: Experimentations and tools table of contents
Pages 7-14  
Year of Publication: 2008
ISBN:978-1-60558-236-8
Authors
Emilio Ancillotti  IIT - CNR, Pisa, Italy
Raffaele Bruno  IIT-CNR, Pisa, Italy
Marco Conti  IIT-CNR, Pisa, Italy
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

In this paper we present an experimental study conducted in 802.11-based mesh networks of three existing rate adaptation algorithms. The aim of this study is twofold. On the one hand, we explore the ability of these algorithms to cope with moderate to high medium contention levels. On the other hand, we investigate their performance on medium-distance 802.11 links. Our study indicates that, in congested networks, the network throughput can degrade up to ten times with respect to the best performance if the rate decision process is based solely on frame loss rates, without differentiating between the various causes of losses (i.e., channel errors or collisions). In addition, we have shown that these rate adaptation strategies perform reasonably well when the time correlation between channel errors is at least of the order of the sampling period used to estimate the channel dynamics. We believe that this study can be useful to derive correct guidelines for the design of new optimized rate adaptation algorithms taking into consideration the above factors.


REFERENCES

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J. Bicket. Bit-rate Selection in Wireless Networks, February, 2005. Massachusetts Intitute of Technology, M.S. Thesis.
4
 
5
 
6
R. Bruno, M. Conti, and E. Gregori. Mesh Networks: Commodity Multihop Ad Hoc Networks. IEEE Commun. Mag., 43(3):123--131, March 2005.
7
8
 
9
 
10
11
 
12
M. Genetzakis and V. Siris. A Contention-Aware Routing Metric for Multi-rate Multi-Radio Mesh Networks. In Proc. of SECON 2008, 2008.
13
 
14
IEEE WG 802.11. IEEE Standard for Information technology-Telecommunications and information exchange between systems-Local and metropolitan area networks-Specific requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, June 12 2007.
 
15
A. Kamerman and L. Monteban. WaveLAN-II: A High-performance wireless LAN for the unlicensed band. Bella Lab Technical Journal, pages 118--133, Summer, 1997.
 
16
J. Kim, S. Kim, S. Choi, and D. Qiao. CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs. In Proc. INFOCOM 2006, pages 1--11, Barcelona, Spain, April 23-29, 2006.
17
 
18
H. Lundgren, K. Ramachandran, E. Belding-Royer, K. Almeroth, M. Benny, A. Hewatt, A. Touma, and A. Jardosh. Experiences from the Design, Deployment, and Usage of the UCSB MeshNet Testbed. IEEE Wireless Commun. Mag., 13(2):18--29, April 2006.
 
19
MadWifi driver documentation. Onoe Rate Control. http://madwifi.org/wiki/UserDocs/RateControl.
 
20
MADWIFI Driver Specification. Multiband Atheros Driver For WIFI. http://madwifi.org/.
 
21
S. Pal, S. Kundu, K. Basu, and S. Das. IEEE 802.11 Rate Control Algorithms: Experimentation and Performance Evaluation in Infrastructure Mode. In Proc. Passive and Active Measurement Conference (PAM) 2006, Adelaide, Australia, March 30--31, 2006.
 
22
Q. Pang, V. Leung, and S. Liew. A Rate Adaptation Algorithm for IEEE 802.11 WLANs Based on Mac-Layer Loss Differentiation. In Proc. BROADNETS 2005, pages 709--717, Boston, Massachusetts, USA, October 3-5, 2005.
 
23
J. Pavon and S. Choi. Link Adaptation Strategy for IEEE 802.11 WLAN via Received Signal Strength Measurement. In Proc. ICC'03, volume 2, pages 1108--1113, Seattle, WA, USA, May 20-30, 2003.
 
24
25
 
26
S. Wang and A. Helmy. BEWARE: Background Traffic-Aware Rate Adaptation for IEEE 802.11 MAC. In Proc. WoWMoM 2008, New Port Beach, CA, USA, June 23-27, 2008.
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Collaborative Colleagues:
Emilio Ancillotti: colleagues
Raffaele Bruno: colleagues
Marco Conti: colleagues