| 引用本文: | 候松松,胡旭东,戴宁,俞博,方辽辽,沈春娅,马惠东.基于PSO-SA算法的纺纱数据采集时延优化研究[J].软件工程,2025,28(9):50-55.【点击复制】 |
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| 摘 要: 针对现阶段纺纱数据采集中数据量激增导致传输时延较大和数据缺失问题,设计了一种基于优先级的纺纱数据采集时延优化策略。该策略采用云-边-端协同架构,结合粒子群算法(PSO)与模拟退火算法(SA),实现任务优先级管理、动态任务分配和资源分配,确保数据采集时延最小化和关键数据的实时传输。实验结果表明,该策略显著减少了数据传输时间和数据丢失情况,提高了系统的响应速度与数据处理的可靠性,有效支撑纺纱生产过程的高效运行。 |
| 关键词: 纺纱设备 数据采集 优先级 时延优化 粒子群模拟退火算法 |
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中图分类号:
文献标识码: A
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| 基金项目: 浙江省科技计划项目(2022C01065) |
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| Research on Spinning Data Acquisition Latency Optimization Based on PSO-SA Algorithm |
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HOU Songsong1, HU Xudong1, DAI Ning1, YU Bo1, FANG Liaoliao1, SHEN Chunya2, MA Huidong3
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(1.School of Mechanical Engineering, Zhejiang Sc-i Tech University, Hangzhou 310018, China;
2.Zhejiang Tianheng Information Technology CO., Ltd., Shaoxing 312500, China;
3.Zhejiang Kangli Automation Technology Co., Ltd., Shaoxing 312500, China)
2059866938@qq.com; xdhu@zstu.edu.cn; zstudn@zstu.edu.cn; 513665714@qq.com;; 1152862843@qq.com; cyshen@k-l tec.com.cn; hd.ma@139.com
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| Abstract: To address the issues of significant transmission delays and data loss caused by the surge in data volume during spinning data acquisition, this study designs a priority-based latency optimization strategy. The strategy employs a cloud-edge-end collaborative architecture, integrating Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms. It achieves task priority management, dynamic task allocation, and resource distribution to minimize data acquisition latency and ensure rea-l time transmission of critical data. Experimental results demonstrate that this strategy significantly reduces data transmission time and data loss rates, enhances system response speed and data processing reliability, thereby effectively supporting the efficient operation of spinning production processes. |
| Keywords: spinning equipment data acquisition priority latency optimization PSO-SA algorithm |
