安全云端协作中的优化数据存储 容错方法

M. Manideepsai, U. Vineeth Goud, CH. Vinay Goud, P. Vignesh Yadav, D. Saidulu
{"title":"安全云端协作中的优化数据存储 容错方法","authors":"M. Manideepsai, U. Vineeth Goud, CH. Vinay Goud, P. Vignesh Yadav, D. Saidulu","doi":"10.32628/ijsrset2411255","DOIUrl":null,"url":null,"abstract":"The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.","PeriodicalId":14228,"journal":{"name":"International Journal of Scientific Research in Science, Engineering and Technology","volume":"108 46","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Optimized Data Storage in A Secure Cloud-Edge Collaboration  A Fault Tolerance Approach\",\"authors\":\"M. Manideepsai, U. Vineeth Goud, CH. Vinay Goud, P. Vignesh Yadav, D. Saidulu\",\"doi\":\"10.32628/ijsrset2411255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.\",\"PeriodicalId\":14228,\"journal\":{\"name\":\"International Journal of Scientific Research in Science, Engineering and Technology\",\"volume\":\"108 46\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Scientific Research in Science, Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32628/ijsrset2411255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Scientific Research in Science, Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32628/ijsrset2411255","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

边缘智能物联网设备的兴起带动了边缘存储系统(ESS)的发展,以实现对海量边缘数据的高效访问。ESS 可以减轻云中心的负荷,改善用户体验。然而,ESS 在提高容错性和效率方面仍面临挑战。因此,需要一种安全高效的容错存储方案。现有方案存在边缘存储开销大、难以保护边缘数据隐私、数据写入性能低等缺点。为解决这些问题,我们提出了分层云边缘协作容错存储(HCEFT)模型。该模型旨在增强系统鲁棒性、减少边缘存储开销并确保边缘数据隐私。我们还介绍了一种 HCEFT 中数据写入的优化方法,称为 ECWSS(基于 Steiner 树和 SDN 的擦除码数据写入方法)。这种方法改进了数据写入时间和流量消耗之间的权衡。我们的方案提高了数据的稳健性、可用性和安全性。此外,写入优化方法可将数据写入时间减少 13%-67%,将网络流量消耗减少 20%-62%,从而提高网络负载平衡性能。
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
An Optimized Data Storage in A Secure Cloud-Edge Collaboration  A Fault Tolerance Approach
The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.
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
UGC Guidelines on Sustainable and Vibrant University- Industry Linkage System for Indian Universities, 2024 Leachate as a Fertilizer Artificial Intelligence in Healthcare : A Review Advancements in Quadcopter Development through Additive Manufacturing: A Comprehensive Review Sensing Human Emotion using Emerging Machine Learning Techniques
×
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