在边缘处线性化低延迟读取

Joshua Guarnieri, Aleksey Charapko
{"title":"在边缘处线性化低延迟读取","authors":"Joshua Guarnieri, Aleksey Charapko","doi":"10.1145/3578358.3591327","DOIUrl":null,"url":null,"abstract":"Edge computing enables moving data closer to users to reduce latency and improve user experience. Edge data centers are capable and reliable enough to support various data management solutions, such as caches and data stores. Unfortunately, edge storage systems sacrifice consistency to benefit from geographical proximity to users. In this paper, we present EdgePQR, a strongly consistent, edge-aware data store that allows edge clients to read \"hot\" data locally at the edge with low latency. EdgePQR relies on the piece-wise defined quorums consisting of nodes in a core cloud system and one or more edge data centers to replicate data to the edge. It then uses an edge quorum to query data locally. EdgePQR ensures safety by enforcing intersections between all vital quorums: any leader election and replication quorums intersect, and any replication and edge-read quorums intersect as well.","PeriodicalId":198398,"journal":{"name":"Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Linearizable Low-latency Reads at the Edge\",\"authors\":\"Joshua Guarnieri, Aleksey Charapko\",\"doi\":\"10.1145/3578358.3591327\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge computing enables moving data closer to users to reduce latency and improve user experience. Edge data centers are capable and reliable enough to support various data management solutions, such as caches and data stores. Unfortunately, edge storage systems sacrifice consistency to benefit from geographical proximity to users. In this paper, we present EdgePQR, a strongly consistent, edge-aware data store that allows edge clients to read \\\"hot\\\" data locally at the edge with low latency. EdgePQR relies on the piece-wise defined quorums consisting of nodes in a core cloud system and one or more edge data centers to replicate data to the edge. It then uses an edge quorum to query data locally. EdgePQR ensures safety by enforcing intersections between all vital quorums: any leader election and replication quorums intersect, and any replication and edge-read quorums intersect as well.\",\"PeriodicalId\":198398,\"journal\":{\"name\":\"Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3578358.3591327\",\"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 10th Workshop on Principles and Practice of Consistency for Distributed Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3578358.3591327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

边缘计算使数据更接近用户,从而减少延迟并改善用户体验。边缘数据中心的能力和可靠性足以支持各种数据管理解决方案,如缓存和数据存储。不幸的是,边缘存储系统牺牲了一致性,从而受益于与用户的地理位置接近。在本文中,我们提出了EdgePQR,这是一种强一致性、边缘感知的数据存储,允许边缘客户端以低延迟在边缘本地读取“热”数据。EdgePQR依赖于由核心云系统中的节点和一个或多个边缘数据中心组成的分段定义仲裁来将数据复制到边缘。然后,它使用边缘仲裁在本地查询数据。EdgePQR通过强制所有重要群体之间的交叉来确保安全性:任何leader选举和复制群体都会相交,任何复制群体和边缘读取群体也会相交。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Linearizable Low-latency Reads at the Edge
Edge computing enables moving data closer to users to reduce latency and improve user experience. Edge data centers are capable and reliable enough to support various data management solutions, such as caches and data stores. Unfortunately, edge storage systems sacrifice consistency to benefit from geographical proximity to users. In this paper, we present EdgePQR, a strongly consistent, edge-aware data store that allows edge clients to read "hot" data locally at the edge with low latency. EdgePQR relies on the piece-wise defined quorums consisting of nodes in a core cloud system and one or more edge data centers to replicate data to the edge. It then uses an edge quorum to query data locally. EdgePQR ensures safety by enforcing intersections between all vital quorums: any leader election and replication quorums intersect, and any replication and edge-read quorums intersect as well.
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
期刊最新文献
Verify, And Then Trust: Data Inconsistency Detection in ZooKeeper Data Management for mobile applications dependent on geo-located data A Study of Semantics for CRDT-based Collaborative Spreadsheets AMC: Towards Trustworthy and Explorable CRDT Applications with the Automerge Model Checker Probabilistic Causal Contexts for Scalable CRDTs
×
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:481959085
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