无线MEC系统中队列状态感知的卸载和传输联合优化

doi:10.13190/j.jbupt.2018-256

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (3): 14-20.doi: 10.13190/j.jbupt.2018-256

无线MEC系统中队列状态感知的卸载和传输联合优化

滕颖蕾¹, 刘薇¹, 欧阳卫平², 李鹍³, 宋梅¹

1. 北京邮电大学电子工程学院, 北京 100876;
2. 华为技术有限公司, 深圳 518129;
3. 中国铁道科学研究院集团有限公司标准计量研究所, 北京 100081

收稿日期:2018-10-16 出版日期:2019-06-28 发布日期:2019-06-20
作者简介:滕颖蕾(1983-),女,副教授,博士生导师,E-mail:lilytengtt@bupt.edu.cn.
基金资助:
国家重点研发计划项目（2018YFB1201500）；国家自然科学基金项目（61771072）；北京市自然科学基金项目（L171011）；北京市重大专项项目（Z181100003118012）；中国铁路总公司科技研究开发计划项目（J2018G004）

Queue-Aware Joint Optimization of Offloading and Transmission in Wireless Mobile Edge Computing Systems

TENG Ying-lei¹, LIU Wei¹, OUYANG Wei-ping², LI Kun³, SONG Mei¹

1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Huawei Technologies CO., LTD, Shenzhen 518129, China;
3. Institute of Standard Metrology, China Academy of Railway Sciences, Beijing 100081, China

Received:2018-10-16 Online:2019-06-28 Published:2019-06-20

摘要/Abstract

摘要： 针对多用户-多移动边缘计算服务器系统的动态计算任务卸载问题，基于用户端和服务器端的任务队列模型，以系统的长期平均时延和长期平均功耗为优化目标，求解最优的卸载策略及相应的上行预编码.通过李雅普诺夫优化方法将长期平均问题转化成单阶段目标优化问题，考虑到卸载策略和预编码之间存在范数约束关系，通过连续近似和半正定松弛，可转化成典型的DC规划求预编码解问题.仿真结果表明，所提方案比传统方法具有更低的时延和功耗.

关键词: 移动边缘计算, 预编码, 李雅普诺夫优化, 凸优化

Abstract: Considering task queue model on both user and mobile edge computing (MEC) server side, a dynamic computing task offloading problem in multi-user-multi-MEC-server system is proposed. To find the optimal offloading and corresponding uplink precoding strategy, a long-term average overhead containing delay and power consumption of the whole system optimization problem is formulated. The original problem is transformed into a single-stage cost target optimization problem based on Lyapunov optimization method and further converted into a typical DC programming problem by utilizing successive approximation and semi-definite relaxation. Simulation shows that the proposed scheme characterized by optimizing precoding design can meet the lower delay and power consumption requirements.

Key words: mobile edge computing, precoding, Lyapunov optimization, convex optimization

中图分类号:

TN929.53

滕颖蕾, 刘薇, 欧阳卫平, 李鹍, 宋梅. 无线MEC系统中队列状态感知的卸载和传输联合优化[J]. 北京邮电大学学报, 2019, 42(3): 14-20.

TENG Ying-lei, LIU Wei, OUYANG Wei-ping, LI Kun, SONG Mei. Queue-Aware Joint Optimization of Offloading and Transmission in Wireless Mobile Edge Computing Systems[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(3): 14-20.

参考文献

[1] Blanco B, Fajardo J O, Giannoulakis I, et al.Technology pillars in the architecture of future 5G mobile networks:NFV, MEC and SDN[J].Computer Standards & Interfaces, 2017, 54(4):216-228.
[2] Wang Chenmeng, Yu F R, Liang Chengchao, et al.Joint computation offloading and interference management in wireless cellular networks with mobile edge computing[J].IEEE Transactions on Vehicular Technology, 2017, 66(8):7432-7445.
[3] Xu Jie, Sun Yuxuan, Chen Lixing, et al.E2M2:energy efficient mobility management in dense small cells with mobile edge computing[C]//IEEE International Conference on Communications(ICC).New York:IEEE Press, 2017:17065927.
[4] Han Kaifeng, Ko S W, Huang Kaibin.Spatial modeling and latency analysis for mobile edge computing in wireless networks[C]//IEEE International Conference on Communications (ICC).New York:IEEE Press, 2018:17971408.
[5] Cheng Kang, Teng Yinglei, Sun Weiqi, et al.Energy-efficient joint offloading and wireless resource allocation strategy in multi-MEC server systems[C]//IEEE International Conference on Communications (ICC).New York:IEEE Press, 2018:8422877.
[6] Wang Wei, Lau V K N, Peng Mugen.Delay-aware uplink Fronthaul allocation in cloud radio access networks[J].IEEE Transactions on Wireless Communications, 2017, 16(7):4275-4287.
[7] Li Jian, Wu Jingxian, Peng Mugen, et al.Queue-aware joint Remote radio head activation and beamforming for green cloud radio access networks[C]//IEEE Global Communications Conference.New York:IEEE Press, 2015:15808266.
[8] Chen M H, Liang Ben, Dong Min.Joint offloading decision and resource allocation for multi-user multi-task mobile cloud[C]//IEEE International Conference on Communications(ICC).New York:IEEE Press, 2016:16141619.
[9] Wu Xiaoxiao, So A, Pan Jiaxian, et al.Semidefinite relaxation and approximation analysis of a beamformed alamouti scheme for relay beamforming networks[J].IEEE Transactions on Signal Processing, 2017, 65(9):2428-2443.

[1]	魏明亮耿绥燕赵雄文胡玮范静怡. 超密集网络中移动边缘计算的资源分配和任务卸载联合优化研究[J]. 北京邮电大学学报, 2023, 46(2): 50-56.
[2]	付志远施丽琴叶迎晖卢光跃. 反向散射辅助的无线供能NOMA-MEC网络中公平性优化研究[J]. 北京邮电大学学报, 2023, 46(2): 71-77.
[3]	李松王新荣王博文孙彦景陈瑞瑞. 基于随机网络演算的车联网边缘计算性能分析[J]. 北京邮电大学学报, 2022, 45(5): 16-22.
[4]	郅佳琳, 王楠, 满毅, 滕颖蕾. 面向硬件感知的边缘计算卸载和资源分配[J]. 北京邮电大学学报, 2022, 45(2): 22-28.
[5]	杜梅, 周军华, 李敦桥, 陈士钊, 魏翼飞. MEC计算卸载与资源分配联合智能优化方案[J]. 北京邮电大学学报, 2022, 45(2): 65-71.
[6]	张雨晴, 李云, 黄鸿锐, 庄宏成. 异构网络中任务卸载与资源分配联合优化算法[J]. 北京邮电大学学报, 2022, 45(2): 91-97.
[7]	郑远鹏, 张天魁, 朱光宇, 沈鸿. MEC系统中面向网络切片的3C联合资源分配算法[J]. 北京邮电大学学报, 2021, 44(5): 41-47.
[8]	陈东华, 朱旋. 多小区多播无线携能通信鲁棒信干噪比平衡[J]. 北京邮电大学学报, 2021, 44(5): 55-60.
[9]	郝万明, 姚壮, 孙钢灿, 朱政宇, 周一青. 一种优化基站服务状态的C-RAN联合波束设计[J]. 北京邮电大学学报, 2021, 44(3): 41-46.
[10]	康曼聪, 李曦, 纪红, 张鹤立. 基于任务间依赖关系的小小区协作卸载策略[J]. 北京邮电大学学报, 2021, 44(1): 72-78.
[11]	薛建彬, 白子梅. 边缘计算中移动终端安全高效认证协议[J]. 北京邮电大学学报, 2021, 44(1): 110-116.
[12]	赵伟, 王斌, 鲍慧, 赵品芳, 李保罡. 基于mMIMO的MEC安全节能资源分配方法[J]. 北京邮电大学学报, 2020, 43(6): 126-131.
[13]	马璐, 刘铭, 李超, 路兆铭, 马欢. 面向6G边缘网络的云边协同计算任务调度算法[J]. 北京邮电大学学报, 2020, 43(6): 66-73.
[14]	薛建彬, 刘星星, 丁雪乾. 移动边缘计算中基于能量收集的能效优化方案[J]. 北京邮电大学学报, 2020, 43(5): 15-20.
[15]	李民政, 丁健, 刘宁, 王浩. Massive-MIMO系统中能效和频效的性能折中方法[J]. 北京邮电大学学报, 2020, 43(4): 61-67.

无线MEC系统中队列状态感知的卸载和传输联合优化

Queue-Aware Joint Optimization of Offloading and Transmission in Wireless Mobile Edge Computing Systems

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价