基于内存关联分析的预拷贝迁移优化策略

内存预拷贝迁移在密集型负载下存在内存脏页反复传输的问题,导致迭代轮数较多且大幅降低了内存预拷贝迁移的整体性能。脏页概率预测能够有效减少内存脏页反复传输的现象,然而现有脏页概率预测研究都只关注时间相关性而未考虑内存之间的空间相关性。针对该问题,提出一种基于内存关联分析的预拷贝迁移策略。通过脏页率对脏页下一轮变脏概率进行预测,设计Memory_cor算法计算出脏页的关联规则和关联内存页,避免变脏概率大的内存页及其关联内存页传输。实验结果表明,该策略在总迁移时间和停机时间上优于Xen预拷贝迁移方法。

Optimization Strategy for Pre-copy Migration Based on Memory Association Analysis

Memory pre-copy has the problem of repeated transmission of dirty pages under intensive load,which needs a large number of iterations that greatly reduce the overall performance of memory pre-copy migration.The probability prediction of dirty pages can effectively reduce the repeated transmission of dirty pages.However,the existing probability prediction research of dirty pages only focuses on the time correlation while ignoring the spatial correlation between memories.To address this problem,this paper proposes a pre-copy migration strategy based on memory association analysis.The dirty page rate is used to predict the probability of dirty page becoming dirty in the next round.The Memory_cor algorithm is designed to calculate the association rules and associated memory pages of dirty pages,so as to avoid the transmission of memory pages with high dirty probability as well as their associated memory pages.Experimental results show that the proposed strategy is superior to the Xen pre-copy migration method in terms of total migration time and downtime.