Queue Management for the Heavy-Tailed Traffics

T. Nakashima
{"title":"Queue Management for the Heavy-Tailed Traffics","authors":"T. Nakashima","doi":"10.1504/IJSSC.2012.049992","DOIUrl":null,"url":null,"abstract":"The purpose of this research is to design the new queueing algorithm effectively controlling the heavy-tailed traffics based on the comparison between the performance of the passive queue algorithm and that of the active queue algorithm. We adopted the tail-drop algorithm for PQM and the Random Early Detection (RED) for AQM, and conducted the experiments using ns-2 simulator. As the results, we extracted the following features. Firstly, the different $\\alpha$ of the Pareto distribution made the completely different throughput performance. Secondly, the heavy-tailed traffic could improve the throughput performance for both queueing management systems even if the average of file size of distribution increases. Thirdly, RED could effectively reduce the overall load leading the throughput increase and provided the fairness in terms of the throughput. Finally, if the traffic pattern could be changed to the heavy-tailed distribution, the performance could improve.","PeriodicalId":196401,"journal":{"name":"2010 International Conference on Broadband, Wireless Computing, Communication and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Broadband, Wireless Computing, Communication and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSSC.2012.049992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

The purpose of this research is to design the new queueing algorithm effectively controlling the heavy-tailed traffics based on the comparison between the performance of the passive queue algorithm and that of the active queue algorithm. We adopted the tail-drop algorithm for PQM and the Random Early Detection (RED) for AQM, and conducted the experiments using ns-2 simulator. As the results, we extracted the following features. Firstly, the different $\alpha$ of the Pareto distribution made the completely different throughput performance. Secondly, the heavy-tailed traffic could improve the throughput performance for both queueing management systems even if the average of file size of distribution increases. Thirdly, RED could effectively reduce the overall load leading the throughput increase and provided the fairness in terms of the throughput. Finally, if the traffic pattern could be changed to the heavy-tailed distribution, the performance could improve.
重尾流量队列管理
本研究的目的是在比较被动队列算法和主动队列算法性能的基础上,设计一种新的能够有效控制重尾交通的队列算法。我们对PQM采用尾降算法,对AQM采用随机早期检测(RED),并在ns-2模拟器上进行了实验。作为结果,我们提取了以下特征。首先,Pareto分布的不同$\alpha$使得吞吐量性能完全不同。其次,即使分布的平均文件大小增加,重尾流量也可以提高两个队列管理系统的吞吐量性能。第三,RED可以有效地降低导致吞吐量增加的总体负载,并提供吞吐量方面的公平性。最后,如果将流量模式改为重尾分布,性能将得到改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信