混合云环境中的高效能源消耗使用自适应回溯虚拟机整合
S Manikandan1, E Elakiya2, K C Rajheshwari3
1Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, India. profmaninvp@gmail.com.
本研究介绍了虚拟机 (VM) 整合的自适应回溯方法,在混合云环境中显著降低了能源消耗. 新方法实现了95%的准确性,同时降低了高达32%的能源消耗.
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
- 能源效率 能源效率 能源效率
背景情况:
- 虚拟化可以通过虚拟机 (VM) 实现资源共享,但面临着诸如高需求,基础设施问题和服务级别协议 (SLA) 违规等挑战.
- 现有的VM整合方法往往会增加能源消耗和开销,需要更高效的解决方案.
研究的目的:
- 为VM整合提出适应性回溯方法,以尽量减少能源消耗.
- 优化资源利用,降低混合云环境中的运营成本.
主要方法:
- 实现了自适应回溯算法,特别是自适应登和追逐,用于VM整合.
- 在使用Matlab.com的混合云环境中模拟了拟议的方法.
- 基于能源消耗和精度的评估性能.
主要成果:
- 拟议的自适应回溯方法实现了VM整合,与现有方法相比,能源消耗明显降低.
- 该系统的准确度指数为95%.
- 对于多个VM整合,能源消耗减少了28%,30%,32%.
结论:
- 适应式回溯方法为VM整合提供了一种有效的方法,用于在混合云中提高能源效率.
- 拟议的系统为优化资源利用和减少能源足迹提供了可扩展和准确的解决方案.
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