Towards a client-side QoS monitoring and assessment using Generalized Pareto Distribution in a cloud-based environment

A. Kamel, Ala Al-Fuqaha, D. Kountanis, Issa M. Khalil
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引用次数: 8

Abstract

Recently, cloud computing and cloud-based services have been gaining a lot of momentum due to their cost effectiveness. Assuring Quality-of-Service (QoS) guarantees to the cloud's mobile clients is an important and unavoidable problem especially for delay sensitive application like VoIP. In this paper, we propose a novel approach for the early detection of cloud service degradations. The proposed algorithms employ the Generalized Pareto Distribution (GPD) approach to converge to a precise QoS model based on collected delay measurements from the cloud's mobile clients. Our experimental results demonstrate the usefulness of the proposed techniques and their ability to perform early detection of performance degradation of the cloud's infrastructure and its hosted services.
在基于云的环境中使用广义Pareto分布实现客户端QoS监控和评估
最近,云计算和基于云的服务由于其成本效益而获得了很大的发展势头。保证云移动客户端的服务质量(QoS)是一个重要且不可避免的问题,特别是对于像VoIP这样对延迟敏感的应用。在本文中,我们提出了一种早期检测云服务降级的新方法。所提出的算法采用广义帕累托分布(GPD)方法收敛到基于从云的移动客户端收集的延迟测量的精确QoS模型。我们的实验结果证明了所提出的技术的实用性,以及它们对云基础设施及其托管服务的性能退化进行早期检测的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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