边缘服务器计算资源分配方法与仿真实验  

Method and experiments on edge computing resource allocation in smart fishery

作　　者：黄汉英[1] 李鹏飞 HUANG Han-ying;LI Peng-fei(College of Engineering,Huazhong Agricultural University,Wuhan 430070,China)

机构地区：[1]华中农业大学工学院,武汉430070

出　　处：《吉林大学学报(工学版)》2025年第1期316-324,共9页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家重点研发计划项目(2019YFC1606000)。

摘　　要：针对智慧渔业的数据采集传输过程中边缘服务器的带宽资源以及计算资源分配问题,通过求解时延最小化的带约束非线性方程,获得带宽以及计算资源的最优解。在计算资源为10 Gcycles/s、任务数量为40时,比较了粒子群算法、免疫算法、模拟退火算法、灰狼算法、萤火虫算法、序列二次规划算法等优化算法的效果,结果表明序列二次规划算法时延最小,为73.16 s。通过优先分配资源给时延与时延限制比小的任务改进算法,仿真实验结果显示:改进算法时延为56.91 s,较序列二次规划算法减小16.25 s,改进算法在带宽与计算资源分配优化问题中取得的效果更好。For the problem of allocating bandwidth resources as well as computational resources of edge servers during data collection and transmission in smart fishery,the optimal solutions of bandwidth as well as computational resources are obtained by solving the nonlinear equations with constraints for minimizing the time delay.The effect of optimization algorithms such as particle swarm algorithm,immune algorithm,simulated annealing algorithm,gray wolf algorithm,firefly algorithm,and sequential quadratic programming algorithm is compared when the computational resources are 10 Gcycles/s and the number of tasks is 40,and the sequential quadratic programming algorithm has the smallest latency of 73.16 s.By preferentially allocating resources to the task improvement algorithm with small latency to latency constraint ratio,the results show that the time delay of the improved algorithm is 56.91 s,which is 16.25 s less than the sequential quadratic programming algorithm,and the improved algorithm achieves better results in the problem of bandwidth and computational resource allocation optimization.

关 键 词：边缘计算 资源分配 时延限制 序列二次规划 智慧渔业 

分 类 号：S951.2[农业科学—水产养殖]