计算机与数字工程2024，Vol.52Issue(1)：133-139,7.DOI:10.3969/j.issn.1672-9722.2024.01.021
面向大规模AI数据流的接入算法和调度机制
Access Algorithms and Scheduling Mechanisms for Large-Scale AI Data Streams
摘要
Abstract
In the edge access cluster of artificial intelligence data flow,it is important to have higher access bandwidth,but the efficient AI data flow access algorithm and scheduling mechanism can better give full play to the hardware performance such as access server network card.This paper proposes a concurrent access algorithm and scheduling mechanism for large-scale AI data flow.Aiming at the unstable access of AI data unit with dynamic change in size,a area dynamic group access algorithm and a data flow migration and scheduling mechanism based on access server resource prediction are designed.The cluster experiment results show that the area dynamic group access algorithm can better satisfy the access request of large-scale AI data stream.On the prem-ise of ensuring the total concurrency of data flow in the access server cluster,the flow scheduling mechanism based on resource pre-diction makes the utilization of access server resources balanced and greatly reduces the packet loss rate of system AI data unit.关键词
AI数据流/UDP/区域动态分组接入/数据流迁移调度Key words
AI data flow/UDP/area dynamic group access/data flow migration scheduling分类
信息技术与安全科学引用本文复制引用
王季喜,陈庆奎..面向大规模AI数据流的接入算法和调度机制[J].计算机与数字工程,2024,52(1):133-139,7.基金项目
国家自然科学基金项目(编号:61572325) （编号:61572325）
上海重点科技攻关项目(编号:19DZ1208903) （编号:19DZ1208903）
上海智能家居大规模物联共性技术工程中心项目(编号:GCZX14014)资助. （编号:GCZX14014）
