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Cited 6 time in webofscience Cited 9 time in scopus
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A Survey and Comparison of Multichannel Protocols for Performance Anomaly Mitigation in IEEE 802.11 Wireless Networks SCIE SCOPUS

Title
A Survey and Comparison of Multichannel Protocols for Performance Anomaly Mitigation in IEEE 802.11 Wireless Networks
Authors
Sok Hyong KimDong Wook KimSuh, YJ
Date Issued
2013-10
Publisher
John Wiley & Sons
Abstract
Providing multichannel functionality can improve the performance of wireless networks. Although off-the-shelf IEEE 802.11 physical layer and medium access control specifications support multiple channels and multiple data rates, one of the major challenges is how to efficiently utilize available channels and data rates to improve network performance. In multirate networks, low-rate links severely degrade the capacity of high-rate links, which is known as performance anomaly. To overcome the performance anomaly problem, different data rate links can get equal air-time by exploiting time diversity and frequency diversity, or they can be separated over nonoverlapping channels. In this paper, we study existing multichannel protocols proposed to mitigate the performance anomaly problem by classifying them into single-radio protocols, multiradio single-hop protocols, and multiradio multihop protocols. To investigate the effectiveness of multichannel solutions for performance anomaly, we compare these protocols with well-known multichannel protocols that do not consider performance anomaly. In addition, this paper gives insightful research issues to design multichannel protocols that mitigate performance anomaly in IEEE 802.11 wireless networks. Copyright (c) 2012 John Wiley & Sons, Ltd.
Keywords
IEEE 802.11; multichannel; multirate; performance anomaly; wireless networks; MESH NETWORKS
URI
https://oasis.postech.ac.kr/handle/2014.oak/16370
DOI
10.1002/DAC.1396
ISSN
1074-5351
Article Type
Article
Citation
International Journal of Communication Systems, vol. 26, no. 10, page. 1288 - 1307, 2013-10
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서영주SUH, YOUNG JOO
Grad. School of AI
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