Separation and optimization of encryption and erasure coding in decentralized storage systems

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-02-04 DOI:10.1016/j.future.2025.107739
Marcell Szabó , Ákos Recse , Róbert Szabó , Dávid Balla , Markosz Maliosz
{"title":"Separation and optimization of encryption and erasure coding in decentralized storage systems","authors":"Marcell Szabó ,&nbsp;Ákos Recse ,&nbsp;Róbert Szabó ,&nbsp;Dávid Balla ,&nbsp;Markosz Maliosz","doi":"10.1016/j.future.2025.107739","DOIUrl":null,"url":null,"abstract":"<div><div>Entering the cloud storage market requires a high upfront investment, thus it is dominated by a few players with existing capacity. Decentralized cloud storage solutions can disrupt the status quo by allowing businesses and individuals to sell their unused storage capacity, reducing the need for large upfront investments in service infrastructure. We show that network operators providing such service can significantly decrease the traffic volume carried on the transport network, which is essential when serving mobile users, while maintaining high data security by implementing our proposed solution, of leveraging controlled replication inside the core network. Upon data uploads encryption and erasure encoding are separated, with the latter moved inside the network, enabling the arbitrary replication of storable data pieces without straining the access network. We present simulation results, showing that the proposed method reduces traffic by 20% compared to the out-of-the-box solution. Moreover, we elaborate on optimal multi-proxy placements and even optimal storage node choosings in complex ISP networks, where deep data penetration is desired, by giving ILP optimization methods and results, achieving minimal overall network load and maximum data security.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"167 ","pages":"Article 107739"},"PeriodicalIF":6.2000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X25000342","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Entering the cloud storage market requires a high upfront investment, thus it is dominated by a few players with existing capacity. Decentralized cloud storage solutions can disrupt the status quo by allowing businesses and individuals to sell their unused storage capacity, reducing the need for large upfront investments in service infrastructure. We show that network operators providing such service can significantly decrease the traffic volume carried on the transport network, which is essential when serving mobile users, while maintaining high data security by implementing our proposed solution, of leveraging controlled replication inside the core network. Upon data uploads encryption and erasure encoding are separated, with the latter moved inside the network, enabling the arbitrary replication of storable data pieces without straining the access network. We present simulation results, showing that the proposed method reduces traffic by 20% compared to the out-of-the-box solution. Moreover, we elaborate on optimal multi-proxy placements and even optimal storage node choosings in complex ISP networks, where deep data penetration is desired, by giving ILP optimization methods and results, achieving minimal overall network load and maximum data security.

Abstract Image

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
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
期刊最新文献
Editorial Board A self-organized MoE framework for distributed federated learning Keyed watermarks: A fine-grained watermark generation for Apache Flink Fast and Privacy-Preserving Spatial Keyword Authorization Query with access control Performance and efficiency: A multi-generational benchmark of modern processors on bandwidth-bound HPC applications
×
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