Cloud based Content Delivery Network using Genetic Optimization Algorithm for storage cost

S. Sajithabanu, S. Balasundaram
{"title":"Cloud based Content Delivery Network using Genetic Optimization Algorithm for storage cost","authors":"S. Sajithabanu, S. Balasundaram","doi":"10.1109/ANTS.2016.7947822","DOIUrl":null,"url":null,"abstract":"Use of cloud computing technology and its services have pawed its way into many applications and this is also true in case of Content Delivery Networks. The storage services of cloud environment are replacing the traditional Content Delivery Networks for more reliability and easy availability of contents to users. Most research in Content Delivery Networks mainly focuses on delivering contents to the users with less latency and traffic cost. Apart from this the overall cost incurred for the content providers in cases of bandwidth and storage should also be taken into consideration. Most existing Content Delivery Networks focus only on the bandwidth and in some cases latency. In this paper a novel Content Delivery Model is proposed that makes use of a Genetic Optimization Algorithm (GOA) combined with an efficient storage model that can achieve better content placement and delivery in Cloud based Content Delivery Networks. The proposed approach updates itself dynamically to avoid unwanted use of storage that achieves a much better placement of contents thus reducing the storage cost.","PeriodicalId":248902,"journal":{"name":"2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANTS.2016.7947822","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Use of cloud computing technology and its services have pawed its way into many applications and this is also true in case of Content Delivery Networks. The storage services of cloud environment are replacing the traditional Content Delivery Networks for more reliability and easy availability of contents to users. Most research in Content Delivery Networks mainly focuses on delivering contents to the users with less latency and traffic cost. Apart from this the overall cost incurred for the content providers in cases of bandwidth and storage should also be taken into consideration. Most existing Content Delivery Networks focus only on the bandwidth and in some cases latency. In this paper a novel Content Delivery Model is proposed that makes use of a Genetic Optimization Algorithm (GOA) combined with an efficient storage model that can achieve better content placement and delivery in Cloud based Content Delivery Networks. The proposed approach updates itself dynamically to avoid unwanted use of storage that achieves a much better placement of contents thus reducing the storage cost.
基于云的内容分发网络存储成本遗传优化算法
云计算技术及其服务的使用已经深入到许多应用中,内容交付网络也是如此。云环境的存储服务正在取代传统的内容分发网络,为用户提供更可靠、更容易获得的内容。内容交付网络的研究主要集中在如何以更低的时延和流量成本将内容交付给用户。除此之外,内容提供商在带宽和存储方面的总成本也应考虑在内。大多数现有的内容交付网络只关注带宽和某些情况下的延迟。本文提出了一种新的内容交付模型,该模型利用遗传优化算法(GOA)与高效存储模型相结合,可以在基于云的内容交付网络中实现更好的内容放置和交付。所建议的方法动态更新自身,以避免不必要的存储使用,从而实现更好的内容放置,从而降低存储成本。
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