电讯技术2026，Vol.66Issue(2)：202-210,9.DOI:10.20079/j.issn.1001-893x.240705003
基于轨迹预测的D2D辅助边缘计算资源分配和卸载策略
Trajectory Prediction Based Resource Allocation and Offloading Strategy for D2D-assisted Edge Computing
摘要
Abstract
Task offloading and resource allocation are two inextricably linked issues in mobile edge computing(MEC),but the dynamic changes in mobile user location and task requirements bring new challenges to system task offloading and resource allocation.In order to enhance further the quality of user experience and build multi-user multitasking scenarios that support device-to-device(D2D)collaboration,a system cost-minimizing offloading algorithm(TP-CMOA)based on predicting the user trajectory by using unscented Kalman filtering is proposed,and a genetic algorithm and potential game theory are adopted to realize the joint optimization of task offloading strategy and resource allocation strategy.Simulation results show that the proposed algorithm outperforms other benchmark algorithms.关键词
移动边缘计算/设备到设备协作/轨迹预测/资源分配Key words
mobile edge computing/D2D collaboration/trajectory prediction/resource allocation分类
信息技术与安全科学引用本文复制引用
陈怡航,杨守义,郝万明,韩昊锦..基于轨迹预测的D2D辅助边缘计算资源分配和卸载策略[J].电讯技术,2026,66(2):202-210,9.基金项目
国家自然科学基金资助项目(62101499) （62101499）
国家重点研发计划项目(2019YFB1803200) （2019YFB1803200）
