基于强挂起弱预测机制的负载均衡模型研究

发布时间：2018-05-16 17:19

  本文选题：Web服务器集群 + 负载均衡　； 参考：《计算机工程与应用》2017年10期

【摘要】：大数据时代的快速发展和大数据战略的明确提出,使得Web服务器集群将面临更加复杂和严峻的负载挑战。传统的负载均衡算法存在着明显的局限性。提出了一种基于强挂起弱预测机制的负载均衡模型,该模型利用强挂起机制和基于层次分析的三次指数平滑预测算法进行负载均衡动态调度。实验结果表明该模型在系统瞬时性能异常、高并发和重负载交互情况下的负载均衡效果优于传统负载均衡算法。
[Abstract]:With the rapid development of big data era and the clear proposal of big data strategy, Web server cluster will face more complex and severe load challenges. The traditional load balancing algorithm has obvious limitations. A load balancing model based on strong hang and weak prediction mechanism is proposed. The model uses strong hang mechanism and cubic exponential smoothing prediction algorithm based on hierarchical analysis to carry out dynamic load balancing scheduling. The experimental results show that the load balancing effect of this model is better than that of the traditional load balancing algorithm under the condition of abnormal transient performance, high concurrency and heavy load interaction.
【作者单位】： 中国传媒大学;安防大数据处理与应用北京市重点实验室;
【基金】：国家自然科学基金项目(No.6137006)
【分类号】：TP301.6;TP393.09
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本文编号：1897739