计算机应用与软件2026，Vol.43Issue(4)：65-71,7.DOI:10.3969/j.issn.1000-386x.2026.04.009
多边协同计算场景下基于改进麻雀优化的任务卸载策略
TASK OFFLOADING STRATEGY BASED ON IMPROVED SPARROW ALGORITHM IN MULTILATERAL COLLABORATIVE COMPUTING ENVIRONMENT
摘要
Abstract
In the industrial Internet environment,edge computing has the advantage of low communication latency,but it cannot cope well with the demand of multi-device multi-tasking on latency.To address the above problems,we proposed to combine edge computing with cloud computing,built a computation offloading model based on cloud-edge-end collaboration,and introduced an M/M/S queuing model in order to alleviate the computation pressure of edge computing in multi-device multi-tasking scenarios.According to the task queuing,a reasonable task offloading was performed,and a computation offloading strategy based on MS-SSUA was proposed.The experimental results show that the offloading utility of this strategy is stable and more flexible compared with other offloading strategies and reduces the cost of task offloading delay.关键词
多边协同计算/任务计算卸载/MS-SSUA/排队模型Key words
Multilateral collaborative computing/Task computation offloading/MS-SSUA/Queueing model分类
信息技术与安全科学引用本文复制引用
毕堂琪,王剑平,徐启亮..多边协同计算场景下基于改进麻雀优化的任务卸载策略[J].计算机应用与软件,2026,43(4):65-71,7.基金项目
国家重点研发项目(2017YFB0306400) （2017YFB0306400）
云南省科技厅重点项目(202101AS070016). （202101AS070016）
