基于模型的云计算拜占庭故障检测技术

Guisheng Fan, Huiqun Yu, Liqiong Chen, Dongmei Liu
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引用次数: 19

摘要

云计算最近引起了工业界和学术界的极大兴趣。越来越多的互联网应用程序正在向云环境迁移。然而,故障检测技术是云应用中的一个关键问题。这个问题尤其困难,因为云计算本质上依赖于一个高度动态的环境。本文提出了一种基于模型的拜占庭故障检测技术。利用云计算故障网(CFN)对云计算的不同组成部分,如服务资源、云模块、检测和故障过程等进行了精确建模,分析了所构建模型的基本性质。在此基础上,提出了一种能够动态检测云应用执行过程中的故障的故障检测策略。Petri网的操作语义和相关理论证明了其有效性和正确性。通过实例对建模和分析过程进行了仿真,并通过一系列实验验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model Based Byzantine Fault Detection Technique for Cloud Computing
Cloud computing has attracted much interest recently from both industry and academic. More and more Internet applications are moving to the cloud environment. However, fault detection technique in cloud application is a crucial issue. This issue is especially difficult since cloud computing relies by nature on a highly dynamic environment. In this paper, we propose a model based Byzantine fault detection technique for cloud computing. A cloud computing fault net (CFN) is used to precisely model the different components of cloud computing, such as service resources, cloud module, the detection and failure process, etc, the basic properties of the constructed model are analyzed. Based on this, the fault detection strategy is proposed, which can dynamically detect the fault of cloud application in the execution process. The operational semantics and related theories of Petri nets help prove its effectiveness and correctness. An example is used to simulate the modeling and analyzing process, and a series of experiments are done to explain the effectiveness of proposed method.
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