利用在线社交网络中的本地兴趣

Mike P. Wittie, V. Pejović, Lara B. Deek, K. Almeroth, Ben Y. Zhao
{"title":"利用在线社交网络中的本地兴趣","authors":"Mike P. Wittie, V. Pejović, Lara B. Deek, K. Almeroth, Ben Y. Zhao","doi":"10.1145/1921168.1921201","DOIUrl":null,"url":null,"abstract":"Online Social Networks (OSN) are fun, popular, and socially significant. An integral part of their success is the immense size of their global user base. To provide a consistent service to all users, Facebook, the world's largest OSN, is heavily dependent on centralized U.S. data centers, which renders service outside of the U.S. sluggish and wasteful of Internet bandwidth. In this paper, we investigate the detailed causes of these two problems and identify mitigation opportunities. Because details of Facebook's service remain proprietary, we treat the OSN as a black box and reverse engineer its operation from publicly available traces. We find that contrary to current wisdom, OSN state is amenable to partitioning and that its fine grained distribution and processing can significantly improve performance without loss in service consistency. Through simulations of reconstructed Facebook traffic over measured Internet paths, we show that user requests can be processed 79% faster and use 91% less bandwidth. We conclude that the partitioning of OSN state is an attractive scaling strategy for Facebook and other OSN services.","PeriodicalId":20688,"journal":{"name":"Proceedings of The 6th International Conference on Innovation in Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"141","resultStr":"{\"title\":\"Exploiting locality of interest in online social networks\",\"authors\":\"Mike P. Wittie, V. Pejović, Lara B. Deek, K. Almeroth, Ben Y. Zhao\",\"doi\":\"10.1145/1921168.1921201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online Social Networks (OSN) are fun, popular, and socially significant. An integral part of their success is the immense size of their global user base. To provide a consistent service to all users, Facebook, the world's largest OSN, is heavily dependent on centralized U.S. data centers, which renders service outside of the U.S. sluggish and wasteful of Internet bandwidth. In this paper, we investigate the detailed causes of these two problems and identify mitigation opportunities. Because details of Facebook's service remain proprietary, we treat the OSN as a black box and reverse engineer its operation from publicly available traces. We find that contrary to current wisdom, OSN state is amenable to partitioning and that its fine grained distribution and processing can significantly improve performance without loss in service consistency. Through simulations of reconstructed Facebook traffic over measured Internet paths, we show that user requests can be processed 79% faster and use 91% less bandwidth. We conclude that the partitioning of OSN state is an attractive scaling strategy for Facebook and other OSN services.\",\"PeriodicalId\":20688,\"journal\":{\"name\":\"Proceedings of The 6th International Conference on Innovation in Science and Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"141\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of The 6th International Conference on Innovation in Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1921168.1921201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of The 6th International Conference on Innovation in Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1921168.1921201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 141

摘要

在线社交网络(OSN)是有趣的、受欢迎的、具有社会意义的。他们成功的一个组成部分是他们庞大的全球用户基础。为了向所有用户提供一致的服务,Facebook作为世界上最大的OSN,严重依赖于美国的集中数据中心,这使得美国以外的服务变得缓慢,并且浪费了互联网带宽。在本文中,我们调查了这两个问题的详细原因,并确定了缓解机会。由于Facebook服务的细节仍然是专有的,我们将OSN视为一个黑盒子,并根据公开可用的痕迹对其操作进行逆向工程。我们发现,与目前的认知相反,OSN状态可以进行分区,其细粒度的分布和处理可以显著提高性能,而不会损失服务一致性。通过在测量的互联网路径上模拟重建的Facebook流量,我们表明用户请求的处理速度可以提高79%,使用的带宽减少91%。我们得出结论,OSN状态的分区对于Facebook和其他OSN服务来说是一个有吸引力的扩展策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploiting locality of interest in online social networks
Online Social Networks (OSN) are fun, popular, and socially significant. An integral part of their success is the immense size of their global user base. To provide a consistent service to all users, Facebook, the world's largest OSN, is heavily dependent on centralized U.S. data centers, which renders service outside of the U.S. sluggish and wasteful of Internet bandwidth. In this paper, we investigate the detailed causes of these two problems and identify mitigation opportunities. Because details of Facebook's service remain proprietary, we treat the OSN as a black box and reverse engineer its operation from publicly available traces. We find that contrary to current wisdom, OSN state is amenable to partitioning and that its fine grained distribution and processing can significantly improve performance without loss in service consistency. Through simulations of reconstructed Facebook traffic over measured Internet paths, we show that user requests can be processed 79% faster and use 91% less bandwidth. We conclude that the partitioning of OSN state is an attractive scaling strategy for Facebook and other OSN services.
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