基于分数社会优化的迁移和复制管理算法,用于云计算分布式文件系统中的负载平衡
Manjula Hulagappa Nebagiri1, Latha Pillappa Hnumanthappa1
1Research Scholar, ISE Sambhram Institute of technology, Bangalore, India.
概括
本研究介绍了一种分数社会优化算法 (FSOA),用于改进基于云的分布式文件系统 (DFS) 的数据管理. FSOA有效地平衡工作负载并管理文件副本,提高数据访问和可用性.
科学领域:
- 计算机科学 计算机科学
- 云计算 云计算 云计算 云计算
- 数据管理数据管理
背景情况:
- 有效的数据管理是分布式文件系统 (DFS) 中的一个关键挑战,特别是在云环境中.
- 文件复制对于最小化数据访问时间和增强数据可用性至关重要.
- 当前的方法往往在动态云环境中难以实现有效的负载平衡和资源利用.
研究的目的:
- 在基于云的DFS中设计一种用于复制管理和负载平衡的新算法.
- 优化资源利用,最大限度地减少能源消耗,降低迁移成本.
- 提高整体系统性能和数据可访问性.
主要方法:
- 使用深度模糊集群 (DFC) 将文件分割成块.
- 虚拟机 (VM) 的循环分配到文件块.
- 通过整合社会优化算法 (SOA) 和分数计算 (FC) 来开发分数社会优化算法 (FSOA).
- 负载平衡考虑资源使用,能源消耗和迁移成本等目标.
主要成果:
- 拟议的FSOA实现了最小的负载 (0.299).
- 在FSOA中,成本 (0.395) 和能源消耗 (0.510) 是最小的.
- 该算法导致了最小的开销 (0.358) 和改善的吞吐量 (0.537).
结论:
- 分数社会优化算法 (FSOA) 为云 DFS 中的复制管理和负载平衡提供了有效的解决方案.
- FSOA显著改善了关键性能指标,包括负载,成本,能源消耗,开销和吞吐量.
- DFC和FSOA的整合为优化分布式文件系统提供了一个强大的框架.
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