Stochastic Modeling and Quality Evaluation of Infrastructure-as-a-Service Clouds
Stochastic Modeling and Quality Evaluation of Infrastructure-as-a-Service Clouds
复制标题
基础设施即服务云的随机建模和质量评估
DOI：
10.1109/tase.2013.2276477
复制
发表时间：
2015-01-01
影响因子：
5.6
通讯作者：
Huang, Yu
中科院分区：
文献类型：
--
作者：
Xia, Yunni;Zhou, MengChu;Huang, Yu
云计算是近年来发展起来的一种面向大规模服务共享的复杂系统的新技术，它不同于网格计算系统的资源共享。在云环境中，来自用户的服务请求从提交到完全交付所请求的服务，要经历许多特定于提供商的步骤。由于自动配置机制的复杂性和动态变化的云环境，云的质量建模和分析并不容易。本文提出了一种基于分析模型的方法，通过考虑预期的请求完成时间，拒绝概率和系统开销率作为关键质量指标的云计算结构即服务的质量评估。它还具有对机器的不同预热和冷却策略进行建模的功能，以及识别系统开销和性能之间的最佳平衡的能力。为了验证所提出的模型的正确性，我们获得了模拟的服务质量（QoS）数据，并进行置信区间分析。研究结果可用于帮助设计和优化工业云计算系统。
Cloud computing is a recently developed new technology for complex systems with massive service sharing, which is different from the resource sharing of the grid computing systems. In a cloud environment, service requests from users go through numerous provider-specific steps from the instant it is submitted to when the requested service is fully delivered. Quality modeling and analysis of clouds are not easy tasks because of the complexity of the automated provisioning mechanism and dynamically changing cloud environment. This work proposes an analytical model-based approach for quality evaluation of Infrastructure-as-a-Service cloud by considering expected request completion time, rejection probability, and system overhead rate as key quality metrics. It also features with the modeling of different warm-up and cool-down strategies of machines and the ability to identify the optimal balance between system overhead and performance. To validate the correctness of the proposed model, we obtain simulative quality-of-service (QoS) data and conduct a confidence interval analysis. The result can be used to help design and optimize industrial cloud computing systems.