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针对传统弹性算法存在的系统抖动、伸缩效率低等问题,提出了云环境下的弹性负载均衡方法.该方法采用集中式设计,建立了弹性负载均衡的总体架构,设计了三级缓冲池及缓冲池管理流程,以提高系统扩展效率.针对于实时负载数据的波动性,该方法结合移动均值算法,利用负载周期变化的特点,提出了负载预测算法.并在此基础上,设计了支持节点批量增减的弹性调度算法,控制系统的整体伸缩和任务的分配.最后对比了传统的双阈值弹性集群和使用本方法的弹性负载均衡集群,并对实验结果统计和分析,验证本文提出的云环境下弹性负载均衡方法的有效性.
Aiming at the problems of system jitter and low scalability in traditional elastic algorithms, this paper proposes a method of elastic load balancing in cloud environment.This method uses a centralized design to establish the overall architecture of elastic load balancing, and designs a three-level buffer pool and buffer Pool management process to improve the efficiency of system expansion.According to the volatility of real-time load data, a new load forecasting algorithm is proposed based on the moving average algorithm and the characteristics of the load cycle.On the basis of this, Increase and decrease of the flexible scheduling algorithm to control the overall system scaling and task distribution.Finally, the traditional dual-threshold elastic clustering and elastic load balancing cluster using this method are compared and the experimental results are statistically analyzed and analyzed to verify the proposed cloud environment The effectiveness of the lower elastic load balancing method.