吉林大学学报（信息科学版）2023，Vol.41Issue(6)：1106-1111,6.
基于节点实时负载的开源大数据负载均衡优化算法
Load Balancing Optimization of Open Source Big Data Based on Node Real-Time Load
摘要
Abstract
To ensure stable network access and reduce resource waste,an open-source big data load balancing optimization algorithm based on real-time node load is proposed.An open-source big data node computing capability model is established,timely feedback and adjustments based on the size of node load are provided,the next action based on the number of requests received by servers in the region is predicted,exponential smoothing method is used to calculate the predicted number of server requests per second,the lag deviation problem of first-order exponential smoothing method is improved,and the comprehensive server load is calculated.Add a load agent and load monitor on the node to balance the number of blocks and the load of sharded nodes,and place undeleted shards and blocks into the minimum unit candidate list to achieve load balancing optimization.Through experiments,it has been proven that the proposed algorithm can improve network resource utilization and load balancing,ensuring a more stable and secure network during access.关键词
节点实时负载/开源大数据/负载均衡优化/区域服务器/节点性能Key words
node real-time load/open source big data/load balancing optimization/regional server/node performance分类
信息技术与安全科学引用本文复制引用
滕飞,刘洋,曹芙..基于节点实时负载的开源大数据负载均衡优化算法[J].吉林大学学报（信息科学版）,2023,41(6):1106-1111,6.基金项目
天津市科技政务数据安全保护与应用策略研究科技发展战略研究计划基金资助项目(21ZLZKZF00220) （21ZLZKZF00220）
