基于支持向量机的动态多播拥塞检测方案

Xiaoming Liu, H. Nyongesa, James Connan
{"title":"基于支持向量机的动态多播拥塞检测方案","authors":"Xiaoming Liu, H. Nyongesa, James Connan","doi":"10.1109/ICMLA.2013.45","DOIUrl":null,"url":null,"abstract":"Congestion is one of the most important issues impeding the development and deployment of IP multicast and multicast application in Mobile ad-hoc network (MANETs). In this paper, we propose a situation aware multicast congestion detection scheme with support vector machines in MANETs. We focus on using support vector machines to detect incipient multicast congestion by using structural situation information. In this way, by using a situation aware learning system, we can detect incipient congestion in advance instead of waiting packet loss. The rate adaptation algorithm can reduce the transmission rate only if the loss is classified as a congestion loss. Simulation results show that a support vector machine is an appropriate mechanism for decision making in proactive multicast congestion detection.","PeriodicalId":168867,"journal":{"name":"2013 12th International Conference on Machine Learning and Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"WMCD: A Situation Aware Multicast Congestion Detection Scheme Using Support Vector Machines in MANETs\",\"authors\":\"Xiaoming Liu, H. Nyongesa, James Connan\",\"doi\":\"10.1109/ICMLA.2013.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Congestion is one of the most important issues impeding the development and deployment of IP multicast and multicast application in Mobile ad-hoc network (MANETs). In this paper, we propose a situation aware multicast congestion detection scheme with support vector machines in MANETs. We focus on using support vector machines to detect incipient multicast congestion by using structural situation information. In this way, by using a situation aware learning system, we can detect incipient congestion in advance instead of waiting packet loss. The rate adaptation algorithm can reduce the transmission rate only if the loss is classified as a congestion loss. Simulation results show that a support vector machine is an appropriate mechanism for decision making in proactive multicast congestion detection.\",\"PeriodicalId\":168867,\"journal\":{\"name\":\"2013 12th International Conference on Machine Learning and Applications\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 12th International Conference on Machine Learning and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLA.2013.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 12th International Conference on Machine Learning and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2013.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

拥塞是阻碍IP组播及其在移动自组网(manet)中应用的发展和部署的主要问题之一。在本文中,我们提出了一种基于支持向量机的情景感知多播拥塞检测方案。重点研究了利用结构状态信息,利用支持向量机检测初发的组播拥塞。通过这种方式,我们可以使用情境感知学习系统来提前检测早期拥塞,而不是等待丢包。速率自适应算法只有在被归为拥塞损耗的情况下才能降低传输速率。仿真结果表明,支持向量机是一种适合于主动组播拥塞检测的决策机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WMCD: A Situation Aware Multicast Congestion Detection Scheme Using Support Vector Machines in MANETs
Congestion is one of the most important issues impeding the development and deployment of IP multicast and multicast application in Mobile ad-hoc network (MANETs). In this paper, we propose a situation aware multicast congestion detection scheme with support vector machines in MANETs. We focus on using support vector machines to detect incipient multicast congestion by using structural situation information. In this way, by using a situation aware learning system, we can detect incipient congestion in advance instead of waiting packet loss. The rate adaptation algorithm can reduce the transmission rate only if the loss is classified as a congestion loss. Simulation results show that a support vector machine is an appropriate mechanism for decision making in proactive multicast congestion detection.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信