融合MEC的星地协同网络：架构、关键技术与挑战

doi:10.11959/j.issn.1000-436x.2020082

通信学报 ›› 2020, Vol. 41 ›› Issue (4): 162-181.doi: 10.11959/j.issn.1000-436x.2020082

融合MEC的星地协同网络：架构、关键技术与挑战

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

¹ 北京邮电大学网络与交换国家重点实验室，北京 100876
² 紫金山实验室，江苏南京 211111
³ 中国电子科技集团公司第五十四研究所，河北石家庄 050081

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:
国家重点研发计划基金资助项目(2019YFB1804403);广东省重点研发计划基金资助项目(2018B010113001)

MEC enabled satellite-terrestrial network:architecture,key technique and challenge

Qinqin TANG¹,Renchao XIE^1,²,Xu LIU¹,Yasheng ZHANG³,Ci HE³,Chengcheng LI³,Tao HUANG^1,²

¹ State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
² Purple Mountain Laboratories,Nanjing 211111,China
³ The 54th Research Institute of China Electronics Technology Group Corporation,Shijiazhuang 050081,China

Revised:2020-03-24 Online:2020-04-25 Published:2020-04-30
Supported by:
The National Key Research and Development Program of China(2019YFB1804403);The National Key Research and Development Program of Guangdong Province(2018B010113001)

摘要/Abstract

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。

关键词: 星地协同网络, 边缘计算, 任务调度, 移动性管理

Abstract:

The introduction of mobile edge computing (MEC) technology in satellite-terrestrial networks can effectively improve the quality of user experience and reduce network redundant traffic,but also brings some challenges.Firstly,the basic architecture of satellite-terrestrial networks and MEC technology was introduced.Moreover,the motivation of introducing MEC into satellite-terrestrial networks and the deployment of MEC were discussed.Then,the architecture of MEC enabled satellite-terrestrial networks was proposed,and the key techniques and typical applications were summarized and analyzed.Finally,the key challenges such as task scheduling and mobility management and some open research issues in integrated networks were summarized.It hopes to provide new ideas for future research in this field.

Key words: satellite-terrestrial network, edge computing, task scheduling, mobility management

中图分类号:

TP393

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.

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参考文献 61

[1]	YAO H , WANG L , WANG X ,et al. The space-terrestrial integrated network (STIN):an overview[J]. IEEE Communications Magazine, 2018,56(9): 2-9.
[2]	CASONI M , GRAZIA C A , KLAPEZ M ,et al. Integration of satellite and LTE for disaster recovery[J]. IEEE Communications Magazine, 2015,53(3): 47-53.
[3]	易克初, 李怡, 孙晨华 ,等. 卫星通信的近期发展与前景展望[J]. 通信学报, 2015,36(6): 157-172.
	YI K C , LI Y , SUN C H ,et al. Recent development and its prospect of satellite communications[J]. Journal on Communications, 2015,36(6): 157-172.
[4]	CHIEN W C , LQOS C F , HOSSAIN M S ,et al. Heterogeneous space and terrestrial integrated networks for IoT:architecture and challenges[J]. IEEE Network, 2019,33(1): 15-21.
[5]	ARTIGA X , PEREZ-NEIRA A , BARANDA J ,et al. Shared access satellite-terrestrial reconfigurable backhaul network enabled by smart antennas at mmwave band[J]. IEEE Network, 2018,32(5): 46-53.
[6]	CAO Y , GUO H , LIU J ,et al. Optimal satellite gateway placement in space-ground integrated networks[J]. IEEE Network, 2018,32(5): 32-37.
[7]	DU J , JIANG C , ZHANG H ,et al. Secure satellite-terrestrial transmission over incumbent terrestrial networks via cooperative beamforming[J]. IEEE Journal on Selected Areas in Communications, 2018,36(7): 1367-1382.
[8]	ZHANG J , ZHANG X , IMRAN M A ,et al. Energy efficient hybrid satellite terrestrial 5G networks with software defined features[J]. Journal of Communications ＆ Networks, 2017,19(2): 147-161.
[9]	SANCHEZ M , SELVA D , CAMERON B ,et al. Results of the MIT space communication and navigation architecture study[C]// IEEE Aerospace Conference. Piscataway:IEEE Press, 2014: 1-14.
[10]	OIKONOMOU I . The European defence agency and EU military space policy:whose space odyssey?[J]. Space Policy, 2012,28(2): 102-109.
[11]	JAPAN.Basic plan on space policy,strategic headquarters for space policy[R]. Government of Japan, 2013.
[12]	李凤华, 殷丽华, 吴巍 ,等. 天地一体化信息网络安全保障技术研究进展及发展趋势[J]. 通信学报, 2016(11): 156-168.
	LI F H , YIN L H , WU W ,et al. Research status and development trends of security assurance for space-ground integration information network[J]. Journal on Communications, 2016,37(11): 156-168.
[13]	KUMAR K , LIU J , LU Y H ,et al. A survey of computation offloading for mobile systems[J]. Mobile Networks and Applications, 2013,18(1): 129-140.
[14]	CHEN X . Decentralized computation offloading game for mobile cloud computing[J]. IEEE Transactions on Parallel and Distributed Systems, 2014,26(4): 974-983.
[15]	SHI W , CAO J , ZHANG Q ,et al. Edge computing:vision and challenges[J]. IEEE Internet of Things Journal, 2016,3(5): 637-646.
[16]	DU J , ZHAO L , FENG J ,et al. Computation offloading and resource allocation in mixed fog/cloud computing systems with min-max fairness guarantee[J]. IEEE Transactions on Communications, 2017,66(4): 1594-1608.
[17]	WANG C , YU F R , LIANG C ,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.
[18]	CHANG Z , ZHOU Z , RISTANIEMI T ,et al. Energy efficient optimization for computation offloading in fog computing system[C]// IEEE Global Communications Conference. Piscataway:IEEE Press, 2017: 1-6.
[19]	ETSI. Mobile-edge computing:introductory technical white paper[R]. ETSI White Paper, 2014.
[20]	MACH P , BECVAR Z . Mobile edge computing:a survey on architecture and computation offloading[J]. IEEE Communications Surveys ＆Tutorials, 2017,19(3): 1628-1656.
[21]	WANG S , ZHANG X , ZHANG Y ,et al. A survey on mobile edge networks:convergence of computing,caching and communications[J]. IEEE Access, 2017,5: 6757-6779.
[22]	MAO Y , YOU C , ZHANG J ,et al. A survey on mobile edge computing:the communication perspective[J]. IEEE Communications Surveys ＆ Tutorials, 2017,19(4): 2322-2358.
[23]	LUGLIO M , ROMANO S P , ROSETI C ,et al. Service delivery models for converged satellite-terrestrial 5G network deployment:a satellite-assisted CDN use-case[J]. IEEE Network, 2019,33(1): 142-150.
[24]	KANEV K , MIRENKOV N . Satellite cloud computing[C]// IEEE Workshops of International Conference on Advanced Information Networking and Applications. Piscataway:IEEE Press, 2011: 147-152.
[25]	ZHANG Z , ZHANG W , TSENG F H . Satellite mobile edge computing:improving QoS of high-speed satellite-terrestrial networks using edge computing techniques[J]. IEEE Network, 2019,33(1): 70-76.
[26]	LIU J , SHI Y , FADLULLAH Z M ,et al. Space-air-ground integrated network:a survey[J]. IEEE Communications Surveys ＆ Tutorials, 2018,20(4): 2714-2741.
[27]	CONTI M , GIORDANO S . Mobile ad hoc networking:milestones,challenges,and new research directions[J]. IEEE Communications Magazine, 2014,52(1): 85-96.
[28]	AALAMIFAR F , LAMPE L , BAVARIAN S ,et al. WiMAX technology in smart distribution networks:Architecture,modeling,and applications[C]// IEEE/PES Transmission ＆ Distribution Conference ＆Exposition. Piscataway:IEEE Press, 2014: 1-5.
[29]	DEMESTICHAS P , GEORGAKOPOULOS A , KARVOUNAS D ,et al. 5G on the horizon:key challenges for the radio-access network[J]. IEEE Vehicular Technology Magazine, 2013,8(3): 47-53.
[30]	TALEB T , SAMDANIS K , MADA B ,et al. On multi-access edge computing:a survey of the emerging 5G network edge architecture and orchestration[J]. IEEE Communications Surveys ＆ Tutorials, 2017,19(3): 1657-1681.
[31]	于晓艺, 王珂, 邓中亮 ,等. 融合MEC的卫星网络架构研究[J]. 信息通信技术与政策, 2018(8): 22-27.
	YU X Y , WANG K , DENG Z L ,et al. Research on satellite network architecture based on MEC[J]. Information and Communications Technology and Policy, 2018(8): 22-27.
[32]	谢人超, 廉晓飞, 贾庆民 ,等. 移动边缘计算卸载技术综述[J]. 通信学报, 2018,39(11): 138-155.
	XIE R C , LIAN X F , JIA Q M ,et al. Survey on computation offloading in mobile edge computing[J]. Journal on Communications, 2018,39(11): 138-155.
[33]	ZHANG W , ZHANG Z , CHAO H C . Cooperative fog computing for dealing with big data in the internet of vehicles:architecture and hierarchical resource management[J]. IEEE Communications Magazine, 2017,55(12): 60-67.
[34]	SHUKLA R M , MUNIR A . A computation offloading scheme leveraging parameter tuning for real-time IoT devices[C]// IEEE International Symposium on Nanoelectronic and Information Systems. Piscataway:IEEE Press, 2016: 208-209.
[35]	HA K , PILLAI P , LEWIS G ,et al. The impact of mobile multimedia applications on data center consolidation[C]// IEEE International Conference on Cloud Engineering. Piscataway:IEEE Press, 2013: 166-176.
[36]	CISCO. Cisco visual networking index:global mobile data traffic forecast update 2016-2021 white paper[R]. 2017.
[37]	WANG W , TONG Y , LI L ,et al. Near optimal timing and frequency offset estimation for 5G integrated LEO satellite communication system[J]. IEEE Access, 2019,7: 113298-113310.
[38]	VAQUERO L M , RODERO-MERINO L . Finding your way in the fog:towards a comprehensive definition of fog computing[J]. Computer Communication Review, 2014,44(5): 27-32.
[39]	CAO S , WEI J , HAN H ,et al. Space edge cloud enabling network slicing for 5G satellite network[C]// International Wireless Communications ＆ Mobile Computing Conference.[S.n.:s.l. ], 2019: 787-792.
[40]	WEI J , CAO S . Application of edge intelligent computing in satellite Internet of things[C]// IEEE International Conference on Smart Internet of Things. Piscataway:IEEE Press, 2019: 85-91.
[41]	CHENG N , LYU F , QUAN W ,et al. Space/aerial-assisted computing offloading for IoT applications:a learning-based approach[J]. IEEE Journal on Selected Areas in Communications, 2019,37(5): 1117-1129.
[42]	BI Y , HAN G , XU S ,et al. Software defined space-terrestrial integrated networks:architecture,challenges,and solutions[J]. IEEE Network, 2019,33(1): 22-28.
[43]	LIAO S , DONG M , OTA K ,et al. Vehicle mobility-based geographical migration of fog resource for satellite-enabled smart cities[C]// IEEE Global Communications Conference. Piscataway:IEEE Press, 2018: 1-6.
[44]	ZHANG N , ZHANG S , YANG P ,et al. Software defined space-air-ground integrated vehicular networks:challenges and solutions[J]. IEEE Communications Magazine, 2017,55(7): 101-109.
[45]	MIJUMBI R , SERRAT J , GORRICHO J L ,et al. Network function virtualization:state-of-the-art and research challenges[J]. IEEE Communications Surveys ＆ Tutorials, 2015,18(1): 236-262.
[46]	YE Q , LI J , QU K ,et al. End-to-end quality of service in 5G networks:examining the effectiveness of a network slicing framework[J]. IEEE Vehicular Technology Magazine, 2018,13(2): 65-74.
[47]	TANG F , FADLULLAH Z M , KATO N ,et al. AC-POCA:anticoordination game based partially overlapping channels assignment in combined UAV and D2D-based networks[J]. IEEE Transactions on Vehicular Technology, 2018,67(2): 1672-1683.
[48]	CHENG F , ZHANG S , LI Z ,et al. UAV trajectory optimization for data offloading at the edge of multiple cells[J]. IEEE Transactions on Vehicular Technology, 2018,67(7): 6732-6736.
[49]	ARANITI G , BISIO I , DE SANCTIS M ,et al. Multimedia content delivery for emerging 5G-satellite networks[J]. IEEE Transactions on Broadcasting, 2016,61(2): 1-14.
[50]	ALMUGHALLES W , CHAI R , LIN J ,et al. Task execution latency minimization-based joint computation offloading and cell selection for MEC-enabled HetNets[C]// Wireless and Optical Communications Conference.[S.n.:s.l. ], 2019: 1-5.
[51]	GUO H , LIU J . Collaborative computation offloading for multi-access edge computing over fiber-wireless networks[J]. IEEE Transactions on Vehicular Technology, 2018,67(5): 4514-4526.
[52]	GUO F , ZHANG H , JI H ,et al. An efficient computation offloading management scheme in the densely deployed small cell networks with mobile edge computing[J]. IEEE/ACM Transactions on Networking, 2018,26(6): 2651-2664.
[53]	FOONG K C , . Mobility management for satellite/terrestrial multi-service convergence networks[C]// International Conference on Communication Software ＆ Networks. Piscataway:IEEE Press, 2009: 362-366.
[54]	XU X , KOU B , FEI L ,et al. Study on mobility technologies of space-ground integrated IP network toward GEO satellites[C]// IEEE International Conference on Computer and Communications. Piscataway:IEEE Press, 2016: 1832-1836.
[55]	ZENG Y , ZHANG R , LIM T J . Wireless communications with unmanned aerial vehicles:opportunities and challenges[J]. IEEE Communications Magazine, 2016,54(5): 36-42.
[56]	WANG J , LIU K , NI M ,et al. Learning based mobility management under uncertainties for mobile edge computing[C]// IEEE Global Communications Conference. Piscataway:IEEE Press, 2018: 1-6.
[57]	KSENTINI A , TALEB T , CHEN M . A Markov decision process-based service migration procedure for follow me cloud[C]// IEEE International Conference on Communications. Piscataway:IEEE Press, 2014: 1350-1354.
[58]	XU J , SUN Y , CHEN L ,et al. E2M2:energy efficient mobility management in dense small cells with mobile edge computing[C]// IEEE International Conference on Communications. Piscataway:IEEE Press, 2017: 1-6.
[59]	LI C , ZHANG J , HAENGGI M ,et al. User-centric intercell interference nulling for downlink small cell networks[J]. IEEE Transactions on Communications, 2015,63(4): 1419-1431.
[60]	SANAD I , MICHELSON D G . A framework for heterogeneous satelite constellation design for rapid response earth observations[C]// IEEE Aerospace Conference. Piscataway:IEEE Press, 2019: 1-10.
[61]	CHIEN W , LAI C , HOSSAIN M S ,et al. Heterogeneous space and terrestrial integrated networks for IoT:architecture and challenges[J]. IEEE Network, 2019,33(1): 15-21.

比较项目	种类	高度/km	时延/ms	移动性	路由	传输技术	通信协议	计算效率	覆盖范围	通信代价	发展时间	环境	优势	劣势
	LEO	200~3 000	15	快
卫星网络	MEO	3 000	100	较快	动态	激光、微波	DTN	低	大	高	短	太空、航空	服务覆盖范围广、广播/多播	高传输时延、能力受限、高移动性
	GEO	35 786	250	对地静止
地面网络	光纤	无	5	静止	静态	微波、光纤	TCP/IP	高	小	低	长	航空、海洋、陆地	资源丰富、高吞吐量	服务覆盖范围受限、易受自然灾害影响
	5G	无	约1	静止

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[39]	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[40]	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[25]	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[41]	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[42]	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[43]	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

场景	优化目标	文献	方案	技术方法
	吞吐量	文献[47]	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[48]	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[49]	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[50]	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
移动边缘计算	能耗	文献[51]	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[52]	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[25]	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[41]	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

场景	优化目标	文献	方案	技术方法
	网络可靠性	文献[53]	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[54]	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
星地协同网络	吞吐量和能量	文献[55]	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[56]	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[57]	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
移动边缘计算	计算性能	文献[58]	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[43]	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

融合MEC的星地协同网络：架构、关键技术与挑战

MEC enabled satellite-terrestrial network:architecture,key technique and challenge

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