一个基于云环境中区域之间负载平衡算法的安全解决方案
Sarah Eljack1, Mahdi Jemmali1,2,3, Mohsen Denden4,5
1Department of Computer Science and Information, College of Science at Zulfi, Majmaah University, Majmaah, Saudi Arabia.
PeerJ. Computer science
|December 11, 2023
概括
本研究介绍了一种新的云数据存储模型,通过优化区域和区域选择来最大限度地减少文件传输事件. 拟议的"调度器"组件和"分组方法"算法有效地平衡数据负载,提高敏感信息的安全性.
科学领域:
- 云计算和数据存储的数据存储.
- 信息安全和数据管理信息安全和数据管理
- 算法设计和优化 算法设计和优化
背景情况:
- 在云中存储敏感数据会因为全球网络传输而带来风险,可能会增加安全漏洞.
- 不高效的数据配置可能导致区域之间不必要的文件传输,增加运营成本和复杂性.
- 尽量减少数据迁移对于维护安全和优化云环境中资源利用至关重要.
研究的目的:
- 开发一种用于跨云区域调度文件的新型模型,平衡安全性和负载.
- 通过优化对敏感数据存储的区域和区域选择来最大限度地减少文件传输事件的数量.
- 解决分布式云环境中最佳文件放置的NP难题.
主要方法:
- 提出了一种新的云数据存储模型,其中包括一个"调度器"组件.
- 引入了一种"分组方法",有几种变体,用于生成用于文件调度的新算法.
- 开发和评估了七个初始算法,其中三种组合产生了改进的结果,导致六个选择的算法用于性能分析.
主要成果:
- 在四个类别中测试了1360个实例,使用三个指标来评估算法性能.
- "四个算法的最佳值"表现出卓越的性能,在86.5%的案例中获得最佳结果.
- 性能最好的算法平均间隙为0.021秒,平均运行时间为0.0018秒.
结论:
- 提出的模型和算法有效地解决了云中安全和高效的敏感数据存储的挑战.
- 优化的文件调度可以最大限度地减少数据传输事件,并提高整体云数据管理安全性.
- "四个算法的最佳值"为云数据放置问题提供了强大而高效的解决方案.
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