WAN Optimization Tools, Techniques and Research Issues for Cloud-Based Big Data Analytics

M. Nirmala
{"title":"WAN Optimization Tools, Techniques and Research Issues for Cloud-Based Big Data Analytics","authors":"M. Nirmala","doi":"10.1109/WCCCT.2014.72","DOIUrl":null,"url":null,"abstract":"Increasing data volumes, data replication at offsite, and the greater than ever use of content-rich and Big Data, applications are mandating IT organizations to optimize their network resources. Trends such as Virtualization and Cloud computing further emphasize this requirement of this current era of Big data. To help with this process, companies are increasingly relying on a new generation of WAN optimization Techniques, Appliances, Controllers, Platforms and Products that are displacing standalone physical appliances by offering more scalability, flexibility, and manageability by additional inclusion of software to handle this Big data and bring valuable insights through big data analytics. An optimized WAN environment can increase network reliability, accessibility and availability and improve cost profiles. It also improves the performance and consistency of data backup, replication, and recovery processes. This paper covers the introduction to WAN optimization, prominent WAN optimization techniques, WAN optimization products used for Big data analytics and finally future trends and research Issues of WAN optimization in the ensuing era of Big data.","PeriodicalId":421793,"journal":{"name":"2014 World Congress on Computing and Communication Technologies","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 World Congress on Computing and Communication Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCCCT.2014.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

Increasing data volumes, data replication at offsite, and the greater than ever use of content-rich and Big Data, applications are mandating IT organizations to optimize their network resources. Trends such as Virtualization and Cloud computing further emphasize this requirement of this current era of Big data. To help with this process, companies are increasingly relying on a new generation of WAN optimization Techniques, Appliances, Controllers, Platforms and Products that are displacing standalone physical appliances by offering more scalability, flexibility, and manageability by additional inclusion of software to handle this Big data and bring valuable insights through big data analytics. An optimized WAN environment can increase network reliability, accessibility and availability and improve cost profiles. It also improves the performance and consistency of data backup, replication, and recovery processes. This paper covers the introduction to WAN optimization, prominent WAN optimization techniques, WAN optimization products used for Big data analytics and finally future trends and research Issues of WAN optimization in the ensuing era of Big data.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于云的大数据分析的广域网优化工具、技术和研究问题
不断增加的数据量、异地数据复制以及比以往更多地使用内容丰富的大数据,应用程序要求IT组织优化其网络资源。虚拟化和云计算等趋势进一步强调了当前大数据时代的这一要求。为了帮助实现这一过程,公司越来越依赖于新一代广域网优化技术、设备、控制器、平台和产品,这些设备通过提供更多的可扩展性、灵活性和可管理性来取代独立的物理设备,通过附加的软件来处理这些大数据,并通过大数据分析带来有价值的见解。优化的WAN环境可以提高网络可靠性、可访问性和可用性,并改善成本配置文件。它还可以提高数据备份、复制和恢复过程的性能和一致性。本文将介绍广域网优化、主要的广域网优化技术、用于大数据分析的广域网优化产品以及大数据时代下广域网优化的未来趋势和研究问题。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Security in Wireless Sensor Networks: Key Management Module in EECBKM Infants Disease Prediction Architecture Using Artificial Neural Networks and Digital Image Processing Retinal Image Analysis Using Contourlet Transform and Multistructure Elements Morphology by Reconstruction Automated Secured Disaster Recovery with Hyper-V Replica and PowerShell A Cloud Model for Effective E-Learning
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1