传感技术学报2025，Vol.38Issue(1)：128-134,7.DOI:10.3969/j.issn.1004-1699.2025.01.016
边云协同的视频分析任务卸载优化策略
Optimized Strategy for Video Analysis Task Offloading in Edge-Cloud Collaborative Computing
摘要
Abstract
Video analytics is widely adopted in fields of transportation and security nowadays.However,traditional method of offloading video streams direct to the cloud for processing suffers from problems such as restricted access and high latency.Thus,an edge-cloud collaborative computing architecture is proposed,where some of the video streams are offloaded to the edge server to reduce latency and alleviate the load of cloud.Considering the requirements for accuracy,latency,and energy consumption in video analytics tasks,a strate-gy that simultaneously controls the resolution of video frames,the convolution neural network(CNN)model deployment on the edge serv-er,and the edge-cloud offloading decisions is proposed to maximize video analytics accuracy while satisfying long-term average latency and energy consumption constraints.By utilizing the Lyapunov stochastic optimization theory,the original optimization problem is trans-formed into a series of independent optimization problems in each time slot,which are solved by using ant colony algorithm to obtain dy-namic offloading strategy including the selection of video frame resolution,the CNN models to be deployed on edge servers,and the edge-cloud offloading decisions.Simulation results show that the proposed dynamic offloading strategy achieves higher video analytics accuracy compared to other baseline schemes while satisfying the constraints.关键词
边云协同计算/卸载决策/李雅普诺夫理论/蚁群优化算法/视频分析Key words
edge-cloud collaborative computing/offloading decision/Lyapunov theory/ant colony optimization algorithm/video analytics分类
信息技术与安全科学引用本文复制引用
童佳慧,李越,李燕君,毛科技..边云协同的视频分析任务卸载优化策略[J].传感技术学报,2025,38(1):128-134,7.基金项目
浙江省自然科学基金重点项目(LZ25F020009) （LZ25F020009）
国家自然科学基金项目(61772472) （61772472）
