计算机工程与应用2025，Vol.61Issue(10)：341-349,9.DOI:10.3778/j.issn.1002-8331.2402-0102
IIoT环境下基于蜣螂优化的雾工作流调度算法
Fog Workflow Scheduling Algorithm Based on Dung Beetle Optimizer in IIoT Environment
摘要
Abstract
To solve the problem of increasing makespan and cost caused by existing scheduling algorithms for scheduling tasks in workflows with certain requirements on data security and response time in the IIoT(industrial Internet of things)environment,a task scheduling policy that changes based on the load rate of the fog environment is proposed,and the workflow scheduling problem is solved by using a dung beetle optimizer algorithm.The improved algorithm uses the HEFT(heterogeneous earliest finish time)algorithm to initialize the dung beetle population,which reduces the effect of randomness in the original algorithm.Meanwhile,the algorithm introduces the ideas of mirror reflection and opposition-based learning to improve the search performance of the algorithm.The experimental results show that the algorithm has some improvement in makespan and cost compared with some other traditional scheduling algorithms.关键词
工作流调度/蜣螂优化算法/HEFT算法/反向学习/调度算法/雾计算/工业物联网(IIoT)Key words
workflow scheduling/dung beetle optimizer algorithm/HEFT algorithm/opposition-based learning/scheduling algorithm/fog computing/industrial Internet of things(IIoT)分类
信息技术与安全科学引用本文复制引用
吴宏伟,江凌云..IIoT环境下基于蜣螂优化的雾工作流调度算法[J].计算机工程与应用,2025,61(10):341-349,9.基金项目
江苏省重点研发基金(BE2020084-4). （BE2020084-4）
