基于Hadoop系统的互联网流量测量与分析改进研究

Lena T. Ibrahim, R. Hassan, Kamsuriah Ahmad, Asrul Nizam Asat
{"title":"基于Hadoop系统的互联网流量测量与分析改进研究","authors":"Lena T. Ibrahim, R. Hassan, Kamsuriah Ahmad, Asrul Nizam Asat","doi":"10.1109/ICEEI.2015.7352545","DOIUrl":null,"url":null,"abstract":"By using conventional database management tools, data explosion is one of the most regular triggers for the development of Big Data. This results in increase difficulty for database management and larger datasets from existing applications. The organizations face the challenge to capture, manage and analyze the data in an acceptable period of time due to the increasing size of data sets, ranging from several terabytes to multiple petabytes. The proposed research aims at resolving the problem faced in internet traffic measurement and depth analysis. As there is a wide growth in the internet traffic and high speed access, the system is facing a scalability problem. To overcome this, we are introducing a Hadoop based traffic monitoring system which performs analysis of multi-terabytes (IP, HTTP, TCP, NetFlow) of the internet traffic system in a scalable manner and for in-depth analysis of the problem, the paper shows the different features.","PeriodicalId":426454,"journal":{"name":"2015 International Conference on Electrical Engineering and Informatics (ICEEI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A study on improvement of internet traffic measurement and analysis using Hadoop system\",\"authors\":\"Lena T. Ibrahim, R. Hassan, Kamsuriah Ahmad, Asrul Nizam Asat\",\"doi\":\"10.1109/ICEEI.2015.7352545\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By using conventional database management tools, data explosion is one of the most regular triggers for the development of Big Data. This results in increase difficulty for database management and larger datasets from existing applications. The organizations face the challenge to capture, manage and analyze the data in an acceptable period of time due to the increasing size of data sets, ranging from several terabytes to multiple petabytes. The proposed research aims at resolving the problem faced in internet traffic measurement and depth analysis. As there is a wide growth in the internet traffic and high speed access, the system is facing a scalability problem. To overcome this, we are introducing a Hadoop based traffic monitoring system which performs analysis of multi-terabytes (IP, HTTP, TCP, NetFlow) of the internet traffic system in a scalable manner and for in-depth analysis of the problem, the paper shows the different features.\",\"PeriodicalId\":426454,\"journal\":{\"name\":\"2015 International Conference on Electrical Engineering and Informatics (ICEEI)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Electrical Engineering and Informatics (ICEEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEI.2015.7352545\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Electrical Engineering and Informatics (ICEEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEI.2015.7352545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

摘要

通过使用传统的数据库管理工具,数据爆炸是大数据发展最常见的触发因素之一。这增加了数据库管理和现有应用程序中更大数据集的难度。由于数据集的大小不断增加,从几tb到多个pb,组织面临着在可接受的时间内捕获、管理和分析数据的挑战。本研究旨在解决互联网流量测量和深度分析所面临的问题。随着互联网流量的快速增长和高速接入,系统面临着可扩展性问题。为了克服这个问题,我们介绍了一个基于Hadoop的流量监控系统,该系统以可扩展的方式对多tb (IP, HTTP, TCP, NetFlow)的互联网流量系统进行分析,并对问题进行了深入的分析,本文展示了不同的特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study on improvement of internet traffic measurement and analysis using Hadoop system
By using conventional database management tools, data explosion is one of the most regular triggers for the development of Big Data. This results in increase difficulty for database management and larger datasets from existing applications. The organizations face the challenge to capture, manage and analyze the data in an acceptable period of time due to the increasing size of data sets, ranging from several terabytes to multiple petabytes. The proposed research aims at resolving the problem faced in internet traffic measurement and depth analysis. As there is a wide growth in the internet traffic and high speed access, the system is facing a scalability problem. To overcome this, we are introducing a Hadoop based traffic monitoring system which performs analysis of multi-terabytes (IP, HTTP, TCP, NetFlow) of the internet traffic system in a scalable manner and for in-depth analysis of the problem, the paper shows the different features.
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:604180095
Book学术官方微信