吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (6): 1106-1111.

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基于节点实时负载的开源大数据负载均衡优化算法 

 滕 飞, 刘 洋, 曹 芙   

  1. 天津市科学技术信息研究所 信息技术中心, 天津 300038
  • 收稿日期:2022-11-11 出版日期:2023-11-30 发布日期:2023-12-01
  • 通讯作者: 曹芙(1976— ), 女, 天津人, 天津市科学技术信息研究所副高级工程师, 主要 从事数据治理、 大数据分析研究, (Tel)86-13682110452 E-mail:caofu@ tj. gov. cn
  • 作者简介:滕飞(1990— ), 女, 天津人, 天津市科学技术信息研究所工程师, 主要从事数据治理研究, ( Tel) 86-18222927721 (E-mail)125268889@ qq. com
  • 基金资助:
    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)

Load Balancing Optimization of Open Source Big Data Based on Node Real-Time Load 

TENG Fei, LIU Yang, CAO Fu   

  1. Information Technology Center, Tianjin Institute of Scientific and Technical Information, Tianjin 300038, China
  • Received:2022-11-11 Online:2023-11-30 Published:2023-12-01

摘要: 为保证网络访问稳定, 减少资源浪费, 提出了基于节点实时负载的开源大数据负载均衡优化算法。 建立 开源大数据节点计算能力模型, 按照节点负载大小及时反馈和调整, 根据该区域服务器收到的请求数量预测 下一步行动, 利用指数平滑方法算出每秒服务器请求数量的预测值, 完善一阶指数平滑法滞后偏差问题, 计算 服务器综合负载。 在节点上添加一个负载代理和监控器, 用于平衡组块的数目和分片节点负载, 并将不能删除 的分片和组块放入最小单元候选名单, 实现负载均衡优化。 通过实验证明, 所提算法能提高网络资源利用率和 负载均衡性, 在访问中保证网络更加稳定安全。

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

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.

Key words: node real-time load, open source big data, load balancing optimization, regional server, node performance

中图分类号: 

  • TP393