桂林电子科技大学学报2024，Vol.44Issue(6)：634-641,8.DOI:10.16725/j.1673-808X.202272
一种容器云水平伸缩负载预测方法
A horizontal scaling load forecasting method for container cloud
摘要
Abstract
Underprediction will lead to the decrease of service capability,the increase of request violation rate and rejection rate,and finally the degradation of service quality.In the current research on load prediction strategy of container cloud,there is no effective solution to the problem that network application access request is lost due to prediction failure.A underprediction coping strategy(PFCS)was proposed,and an emergency scaling algorithm(ESA)was proposed based on the PFCS.This strategy can effectively detect the occurrence of prediction failure,activate the emergency prediction model in time,and provide another option for scaling decisionl;This strategy can shorten the failure time of horizontal scaling policy to deal with burst traffic,reduce the request rejection rate,and improve the overall quality of service.The experiment uses real network application traffic data to verify the effectiveness of ESA in improving quality of service.The comparison experiment is used to evaluate the response effect of PFCS on prediction failure.The experimental results show that compared with the scaling strategy using only prediction algorithm,udder the condition of not affecting the prediction accuracy,PFCS can make rejection rates decrease by 19.8％-23.0％on average.The experimental re-sults demonstrate the effectiveness of ESA and PFCS.关键词
容器云/水平伸缩/负载预测/欠预测/伸缩策略Key words
container cloud/horizontal scaling/load prediction/underprediction/scaling strategy分类
信息技术与安全科学引用本文复制引用
张正昕,王勇,刘世嘉..一种容器云水平伸缩负载预测方法[J].桂林电子科技大学学报,2024,44(6):634-641,8.基金项目
国家自然科学基金(61861013) （61861013）
广西创新驱动发展专项_科技重大专项(桂科AA18118031) （桂科AA18118031）
