通信学报 ›› 2020, Vol. 41 ›› Issue (4): 162-181.doi: 10.11959/j.issn.1000-436x.2020082
唐琴琴1,谢人超1,2,刘旭1,张亚生3,何辞3,李诚成3,黄韬1,2
修回日期:
2020-03-24
出版日期:
2020-04-25
发布日期:
2020-04-30
作者简介:
唐琴琴(1994- ),女,广西桂林人,北京邮电大学博士生,主要研究方向为边缘计算、车联网、星地协同网络等|谢人超(1984- ),男,福建南平人,博士,北京邮电大学副教授、硕士生导师,主要研究方向为信息中心网络、移动网络内容分发技术、工业互联网、标识解析技术和移动边缘计算等|刘旭(1996- ),男,安徽阜阳人,北京邮电大学硕士生,主要研究方向为边缘计算、星地协同网络等|张亚生(1969- ),男,河北石家庄人,中国电子科技集团公司第五十四研究所研究员,主要研究方向为卫星网络、卫星移动通信等|何辞(1983- ),女,河北石家庄人,中国电子科技集团公司第五十四研究所高级工程师,主要研究方向为卫星网络、卫星移动通信等|李诚成(1989- ),男,河北石家庄人,博士,中国电子科技集团公司第五十四研究所工程师,主要研究方向为卫星网络、卫星移动通信等|黄韬(1980- ),男,重庆人,博士,北京邮电大学教授,主要研究方向为路由与交换、软件定义网络、内容分发网络等
基金资助:
Qinqin TANG1,Renchao XIE1,2,Xu LIU1,Yasheng ZHANG3,Ci HE3,Chengcheng LI3,Tao HUANG1,2
Revised:
2020-03-24
Online:
2020-04-25
Published:
2020-04-30
Supported by:
摘要:
在星地协同网络中引入移动边缘计算(MEC)技术可有效提高用户体验质量和减少网络冗余流量,同时也带来了一些挑战。首先介绍了星地协同网络和MEC技术的基本架构,并讨论了在星地协同网络中引入MEC技术的动机和MEC的部署问题;然后提出了融合MEC的星地协同网络架构,并对其关键技术及典型应用进行了概述和分析;最后总结归纳了融合网络架构中的任务调度、移动性管理等关键挑战和一些开放性研究问题,期望对该领域的后续研究提出可供借鉴的新思路。
中图分类号:
唐琴琴,谢人超,刘旭,张亚生,何辞,李诚成,黄韬. 融合MEC的星地协同网络:架构、关键技术与挑战[J]. 通信学报, 2020, 41(4): 162-181.
Qinqin TANG,Renchao XIE,Xu LIU,Yasheng ZHANG,Ci HE,Chengcheng LI,Tao HUANG. MEC enabled satellite-terrestrial network:architecture,key technique and challenge[J]. Journal on Communications, 2020, 41(4): 162-181.
表2
融合MEC的星地协同网络架构设计相关研究工作总结归类"
优化目标 | 文献 | 主要贡献 | 支撑技术 | 应用场景 |
以降低时延为优化目标 | 文献[ | 提出了一种基于空间的云-雾卫星网络切片架构,并结合 SDN/NFV技术设计了一种资源管理机制,以使网络切片更加灵活 | 网络切片SDN/NFV | 5G |
文献[ | 提出了一种卫星物联网边缘智能计算架构,并分析了边缘计算和人工智能在图像数据目标检测中的作用 | 人工智能 | 5G/6G、物联网 | |
以降低时延和能耗为优化目标 | 文献[ | 提出了一种融合MEC的星地协同网络架构以提高用户的QoS,并提出了一种协同任务调度方案以降低用户感知的时延和系统能耗 | NFV | 5G |
文献[ | 提出了一种面向物联网的星地协同边缘组网架构,并提出了一种联合资源分配和计算卸载方案 | 云计算 | 物联网 | |
以提高系统性能为优化目标 | 文献[ | 提出了一种软件定义的星地协同组网体系结构,并提出了一种基于边缘计算的网络优化方案以提高网络管理灵活性 | SDN/NFV | 5G |
文献[ | 提出了一种面向智慧城市的星地协同雾计算架构,并设计了一种资源定价的激励方案,以平衡网络资源分配 | 雾计算 | 车联网、物联网 |
表3
任务调度研究方案总结归纳"
场景 | 优化目标 | 文献 | 方案 | 技术方法 |
吞吐量 | 文献[ | 提出了一个结合了无人机和D2D的网络架构解决网络中的信道分配问题 | 基于分布式反协调博弈的信道分配算法 | |
星地协同网络 | 文献[ | 优化无人机航迹 | 迭代算法 | |
满足所有用户的速率要求 | ||||
信道和聚合数据速率 | 文献[ | 基于多播子分组最大满意度指数进行度量利用卫星链路进行流量卸载 | 子分组方法 | |
移动边缘计算 | 时延 | 文献[ | 解决了联合计算卸载和单元选择策略问题提出了优化任务执行等待时间的调度方案 | 搜索方法和 Khun-Munkres算法 |
能耗 | 文献[ | 提出一种通过采用FiWi接入的网络架构考虑移动终端的时延约束和信道约束 | 分布式博弈论算法 | |
文献[ | 优化计算卸载决策和资源分配 | 基于粒子群算法的层次化遗传算法 | ||
考虑计算卸载决策、功率控制和无线资源分配 | ||||
融合网络 | 时延和能耗 | 文献[ | LEO对资源进行整合和分配调度用户计算任务卸载 | 协作计算卸载方法 |
文献[ | 提出了一种联合资源分配和任务调度方法设计了基于深度强化学习的计算卸载算法 | 启发式算法 |
表4
移动性管理研究方案总结归纳"
场景 | 优化目标 | 文献 | 方案 | 技术方法 |
网络可靠性 | 文献[ | 在地面网络中使用Hata模型,在卫星网络中使用统计阴影模型 | 自适应神经模糊推理系统的切换算法 | |
星地协同网络 | 文献[ | 研究位置管理和自动路由维护问题达到 100%路由切换成功率的性能 | 集中式路由控制算法 | |
吞吐量和能量 | 文献[ | 讨论了 UAV 的移动中继技术及信息分发技术,通过利用 D2D通信和UAV移动性实现有效信息分发 | — | |
时延 | 文献[ | 考虑到用户无法精准获取网络信息,解决系统信息不确定性导致的移动性管理问题 | Q学习算法 | |
移动边缘计算 | 文献[ | 设计了基于马尔科夫的虚拟机动态迁移策略,提出了利用控制器协助寻找最佳迁移阈值的方案 | 李雅普诺夫算法 | |
计算性能 | 文献[ | 以用户为中心进行移动性管理,最大化边缘计算性能,保持较低的用户通信能耗 | — | |
融合网络 | 网络负载均衡 | 文献[ | 建立了基于车辆移动性的车辆资源地理迁移模型,提出了一种基于资源定价的车辆路径选择激励方案 | 动态资源迁移算法 |
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