雾计算中瞬态服务器基于agent的容错体系结构

J. P. A. Neto, D. Pianto, C. Ralha
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引用次数: 2

摘要

云数据中心正在探索其空闲资源,并提供虚拟机作为没有可用性保证的临时服务器。现货实例是亚马逊AWS提供的临时服务器,其规则根据供需定义价格。只要当前价格低于用户给出的最高出价,这些实例就会运行。Spot实例越来越多地用于执行计算和内存密集型应用程序。通过使用动态容错机制和适当的策略,用户可以有效地使用现货实例以较低的价格运行应用程序。提出了一种弹性多策略的基于agent的云计算架构。该架构结合了机器学习和统计模型来预测实例生存时间,改进容错参数并减少总执行时间。我们评估了我们的策略,实验证明了高水平的准确性,达到94%的生存预测成功率,这表明该模型可以有效地用于定义执行策略,以防止实际工作条件下撤销事件的失败。
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A Fault-Tolerant Agent-Based Architecture for Transient Servers in Fog Computing
Cloud datacenters are exploring their idle resources and offering virtual machine as transient servers without availability guarantees. Spot instances are transient servers offered by Amazon AWS, with rules that define prices according to supply and demand. These instances will run for as long as the current price is lower than the maximum bid price given by users. Spot instances have been increasingly used for executing computation and memory intensive applications. By using dynamic fault tolerant mechanisms and appropriate strategies, users can effectively use spot instances to run applications at a cheaper price. This paper presents a resilient multi-strategy agent-based cloud computing architecture. The architecture combines machine learning and a statistical model to predict instance survival times, refine fault tolerance parameters and reduce total execution time. We evaluate our strategies and the experiments demonstrate high levels of accuracy, reaching a 94% survival prediction success rate, which indicates that the model can be effectively used to define execution strategies to prevent failures at revocation events under realistic working conditions.
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