基于模糊和马尔科夫链的云服务可信状态的评估
Ming Yang1,2, Rong Jiang1,2, Jia Wang3
1School of Information, Yunnan University of Finance and Economics, Kunming, 650221, China.
Scientific reports
|December 3, 2024
概括
评估云服务可信度对于防止损失至关重要. 本研究介绍了一种层次模型和模糊的-马尔科夫链方法,用于客观可信度评估和预测.
科学领域:
- 计算机科学 计算机科学
- 信息系统信息系统信息系统
- 云计算 云计算 云计算 云计算
背景情况:
- 云服务的可靠性至关重要,因为服务故障可能导致用户损失.
- 现有的方法可能无法充分评估或预测云服务可信度的变化.
研究的目的:
- 建立一个层次模型来评估云服务可信度属性.
- 开发一种客观评估和预测云服务可靠性及其变化的方法.
主要方法:
- 建立了云服务可信度属性的层次模型.
- 云服务可信状态是使用模糊和马尔科夫链来定义的.
- 构建了云服务可信状态的会员功能.
主要成果:
- 拟议的方法有效地评估和预测云服务可靠性及其变化.
- 案例分析证明了该方法的可行性和有效性.
- 该方法解决了模糊评估方法的局限性.
结论:
- 开发的方法为云服务可信度评估提供客观和全面的数据.
- 这项研究为云服务可信度领域提供了重要的参考价值.
- 对于用户和提供商来说,这些发现对于管理云服务可靠性至关重要.
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