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Scalable replica selection based on node service capability for improving data access performance in edge computing environment

机译:基于节点服务能力的可伸缩副本选择,可提高边缘计算环境中的数据访问性能

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The replica strategies in traditional cloud computing often result in excessive resource consumption and long response time. In the edge cloud environment, if the replica node cannot be managed efficiently, it will cause problems such as low user's access speed and low system fault tolerance. Therefore, this paper proposed replica creation and selection strategy based on the edge cloud architecture. The dynamic replica creation algorithm based on access heat (DRC-AH) and replica selection algorithms based on node service capability (DRS-NSC) were proposed. The DRC-AH uses data block as replication granularity and Grey Markov chain to dynamically adjust the number of replicas. After the replica is created, when client receives the user's request, the DRS-NSC selects the best replica node to respond to the user. The experiments show that the proposed algorithms have significant advantages in prediction accuracy, user's request response time, resource utilization, etc., and improve the performance of the system to a certain extent.
机译:传统云计算中的复制策略经常导致过多的资源消耗和较长的响应时间。在边缘云环境中,如果无法有效地管理副本节点,将导致诸如用户访问速度低和系统容错能力低等问题。因此,本文提出了一种基于边缘云架构的副本创建和选择策略。提出了基于访问热的动态副本创建算法(DRC-AH)和基于节点服务能力的副本选择算法(DRS-NSC)。 DRC-AH使用数据块作为复制粒度,并使用Gray Markov链动态调整副本数。创建副本后,当客户端收到用户的请求时,DRS-NSC选择最佳副本节点以响应用户。实验表明,该算法在预测精度,用户请求响应时间,资源利用率等方面具有明显优势,并在一定程度上提高了系统性能。

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