論文

査読有り
2014年

Cross-Layer Performance Evaluation of Random AIFSN Scheme in Densely Deployed WLANs

2014 8TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS)
  • Ryuichi Hirata
  • ,
  • Takayuki Nishio
  • ,
  • Masahiro Morikura
  • ,
  • Koji Yamamoto
  • ,
  • Tomoyuki Sugihara

記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/ICSPCS.2014.7021082
出版者・発行元
IEEE

In densely deployed wireless local area networks (WLANs), the throughput performance of WLANs significantly deteriorates as the number of neighboring WLANs increases due to an increase in frame collision probability. To improve throughput performance, we have studied the random arbitration interframe space number (AIFSN) scheme, which is an extension of the carrier sense multiple access with collision avoidance (CSMA/CA). The use of AIFS, the length of which is determined randomly, virtually divides nodes into contending and noncontending groups and maintains a small number of contending nodes. Our previous studies only focused on the performance of the media access control (MAC) layer.
This paper investigates the transport and application performance of the random AIFSN scheme through a simulation by using the QualNet network simulator. We evaluate the transport layer throughput and the session delay, which is a metric for evaluating the quality of experience (QoE), in simulation scenarios where stations (STAs) use a TCP file transfer application on a WLAN as well as in densely deployed WLANs. Our simulation results indicate that the random AIFSN scheme improves TCP throughput and QoE performances in densely deployed WLANs by 50% compared with the conventional CSMA/CA. Moreover, our research reveals the behavior of the random AIFSN scheme in TCP traffic.

リンク情報
DOI
https://doi.org/10.1109/ICSPCS.2014.7021082
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000380403200034&DestApp=WOS_CPL
ID情報
  • DOI : 10.1109/ICSPCS.2014.7021082
  • Web of Science ID : WOS:000380403200034

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