走向云端的实时分析

Amr Osman, M. El-Refaey, A. Elnaggar
{"title":"走向云端的实时分析","authors":"Amr Osman, M. El-Refaey, A. Elnaggar","doi":"10.1109/SERVICES.2013.36","DOIUrl":null,"url":null,"abstract":"The data explosion and the tremendous growth in the volume of data generated from various IT services places an enormous demand on harnessing and smartly analyzing the generated data and enterprise contents. According to recent studies, it is predicted that the volume of such data will become 26 fold in the next five years. While there might be some existing technologies to support this, industry is frantically exploring new models that lead to more efficient and higher performance solutions. With the aid of cloud computing and high performance analytics such as scalable-parallel machine learning, big data could be the fuel to a smarter cloud-powered IT world. Through our work, we provide a state-of-the-art review of high-performance advanced cloud analytics in the literature in attempt to find the ideal real-time platform for distributed analytic computations.","PeriodicalId":169370,"journal":{"name":"2013 IEEE Ninth World Congress on Services","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Towards Real-Time Analytics in the Cloud\",\"authors\":\"Amr Osman, M. El-Refaey, A. Elnaggar\",\"doi\":\"10.1109/SERVICES.2013.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The data explosion and the tremendous growth in the volume of data generated from various IT services places an enormous demand on harnessing and smartly analyzing the generated data and enterprise contents. According to recent studies, it is predicted that the volume of such data will become 26 fold in the next five years. While there might be some existing technologies to support this, industry is frantically exploring new models that lead to more efficient and higher performance solutions. With the aid of cloud computing and high performance analytics such as scalable-parallel machine learning, big data could be the fuel to a smarter cloud-powered IT world. Through our work, we provide a state-of-the-art review of high-performance advanced cloud analytics in the literature in attempt to find the ideal real-time platform for distributed analytic computations.\",\"PeriodicalId\":169370,\"journal\":{\"name\":\"2013 IEEE Ninth World Congress on Services\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Ninth World Congress on Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SERVICES.2013.36\",\"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 IEEE Ninth World Congress on Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERVICES.2013.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29

摘要

数据爆炸和各种IT服务生成的数据量的巨大增长对利用和智能分析生成的数据和企业内容提出了巨大的需求。根据最近的研究,预计在未来五年内,这类数据的数量将增加26倍。虽然可能有一些现有的技术支持这一点,但业界正在疯狂地探索新的模式,以带来更高效、更高性能的解决方案。在云计算和高性能分析(如可扩展并行机器学习)的帮助下,大数据可能成为更智能的云驱动IT世界的燃料。通过我们的工作,我们在文献中提供了高性能先进云分析的最新综述,试图找到分布式分析计算的理想实时平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Real-Time Analytics in the Cloud
The data explosion and the tremendous growth in the volume of data generated from various IT services places an enormous demand on harnessing and smartly analyzing the generated data and enterprise contents. According to recent studies, it is predicted that the volume of such data will become 26 fold in the next five years. While there might be some existing technologies to support this, industry is frantically exploring new models that lead to more efficient and higher performance solutions. With the aid of cloud computing and high performance analytics such as scalable-parallel machine learning, big data could be the fuel to a smarter cloud-powered IT world. Through our work, we provide a state-of-the-art review of high-performance advanced cloud analytics in the literature in attempt to find the ideal real-time platform for distributed analytic computations.
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