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Towards Resilient Method: An exhaustive survey of fault tolerance methods in the cloud computing environment

机译:朝着弹性方法:云计算环境中容错方法的详尽调查

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摘要

Fault Tolerance (FT) is one of the cloud's very critical problems for providing security assistance. Due to the diverse service architecture, detailed architectures & multiple interrelationships that occur in the cloud, implementation is complicated. A few other previous studies attempt to integrate the different fault tolerance frameworks and solutions suggested for the cloud environment, but some accounts occur to be constrained. This research article provides a detailed survey of the state-of-the-art research on emerging methods of fault tolerance for Cloud Computing & categorizes techniques of fault tolerance into three categories: Reactive Methods, Proactive Methods & Resilient Methods. Reactive Methods allow the system to reach a defect condition but instead attempt to get the device back up. Proactive Methods help to prevent the device from reaching a defective condition by introducing actions to minimize defects before impacting the device. On either side, newly developed Resilient Methods strive to reduce the amount of time a device takes to find from a malfunction. In the Resilient Methods context, Machine Learning and Artificial Intelligence played an important role in mapping the recovery period to a task to be configured. This survey offers a comprehensive and detailed description of the various faults kinds, factors, & different methods to fault tolerance used in the cloud. In light of their Basic Methods & some other specific characteristics, & also offers a Clear study of different tolerance mechanisms for failures & provides a comparative study of the structures under the article. It is noted that approaches of fault tolerance directed to checkpoint restart and replication are mainly included to address the crash faults in the cloud.
机译:容错(ft)是云的一个非常关键的问题之一,用于提供安全援助。由于服务架构多样化,云​​中发生的详细架构和多个相互关系,实现复杂。其他一些先前的研究尝试集成为云环境建议的不同的容错框架和解决方案,但有些帐户会被约束。本研究文章对云计算的最新方法提供了详细的现有研究,并将容错技术分为三类:反应方法,主动方法和弹性方法。无功方法允许系统达到缺陷条件,而是尝试备份设备。主动方法有助于防止设备通过引入在影响设备之前最小化缺陷的动作来达到有缺陷的条件。在任何一方面,新开发的弹性方法都努力减少设备从故障中找到的时间量。在弹性方法上下文中,机器学习和人工智能在将恢复期映射到要配置的任务时发挥着重要作用。本调查提供了对云中使用的容错的各种故障种类,因素和不同方法的全面和详细描述。鉴于其基本方法和其他一些特定特征,并且还对失败的不同公差机制提供了清晰的研究,并提供了文章下结构的比较研究。注意,主要包括指向检查点重启和复制的容错方法以解决云中的崩溃故障。

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