云原生边缘计算：探索与展望

doi:10.11959/j.issn.2096-3750.2021.00206

Abstract

Abstract:

Cloud native computing, featured by low-cost container technology, well fits edge computing.It was proposed to apply cloud native computing to make edge computing resource management and control transparent to application development and operation.Compared with cloud computing, edge computing resources are widely distributed, highly heterogeneous, and fragmented, which called for collaborative resource management and control.According to the development status of cloud native related technologies, through the integration of future networking technologies such as soft were defined network and network function virtualization, a full-stack cloud native based edge computing architecture was proposed.Then, considering the hierarchical characteristics of containers, a low-overhead container deployment optimization problem for resource-limited edge computing was studied.Finally, the development challenges faced by cloud native based edge computing were discussed.

Key words: cloud native, edge computing, container, micro service

CLC Number:

TP393

Deze ZENG, Lvhao CHEN, Lin GU, Yuepeng LI. Cloud native based edge computing: vision and challenges[J]. Chinese Journal on Internet of Things, 2021, 5(2): 7-17.

Figures/Tables 6

符号	定义
$N$	常量集合，服务器集合
$I$	常量集合，容器集合
$L$	常量集合，所有容器包含的层集合
$P_{n}$	服务器 $n \in N$ 的计算资源
$S_{n}$	服务器 $n \in N$ 的存储资源
$B_{n}$	服务器 $n \in N$ 的通信资源
$C_{l}$	容器中的 $l \in L$ 层所占的存储资源
$z_{i}^{l}$	二元常量，容器 $i \in I$ 是否需要层 $l \in L$
$x_{n}^{i}$	二元变量，容器 $i \in I$ 是否被部署在服务器 $n \in N$ 上
$y_{n}^{l}$	二元变量，层 $l \in L$ 是否被部署在服务器 $n \in N$ 上
$d_{i}$	容器 $i \in I$ 所需要的计算资源
$b_{i}$	容器 $i \in I$ 所需要的通信资源

References 21

[1]	XU J , CHEN L X , ZHOU P . Joint service caching and task offloading for mobile edge computing in dense networks[C]// IEEE INFOCOM 2018-IEEE Conference on Computer Communications. Piscataway:IEEE Press, 2018: 207-215.
[2]	CHEN X , JIAO L , LI W Z ,et al. Efficient multi-user computation offloading for mobile-edge cloud computing[J]. IEEE/ACM Transactions on Networking, 2016,24(5): 2795-2808.
[3]	DAI Y Y , XU D , MAHARJAN S ,et al. Joint computation offloading and user association in multi-task mobile edge computing[J]. IEEE Transactions on Vehicular Technology, 2018,67(12): 12313-12325.
[4]	ZHOU Y Q , TIAN L , LIU L ,et al. Fog computing enabled future mobile communication networks:a convergence of communication and computing[J]. IEEE Communications Magazine, 2019,57(5): 20-27.
[5]	QI Y L , TIAN L , ZHOU Y Q ,et al. Mobile edge computing-assisted admission control in vehicular networks:the convergence of communication and computation[J]. IEEE Vehicular Technology Magazine, 2019,14(1): 37-44.
[6]	ZHOU Y Q , LIU L , WANG L ,et al. Service-aware 6G:an intelligent and open network based on the convergence of communication,computing and caching[J]. Digital Communications and Networks, 2020,6(3): 253-260.
[7]	KRóL M , MASTORAKIS S , ORAN D ,et al. Compute first networking:distributed computing meets ICN[C]// The 6th ACM Conference on Information-Centric Networking. New York:ACM Press, 2019: 67-77.
[8]	刘泽宁, 李凯, 吴连涛 ,等. 多层次算力网络中代价感知任务调度算法[J]. 计算机研究与发展, 2020,57(9): 1810-1822.
	LIU Z N , LI K , WU L T ,et al. CATS:cost aware task scheduling in multi-tier computing networks[J]. Journal of Computer Research and Development, 2020,57(9): 1810-1822.
[9]	PORAMBAGE P , OKWUIBE J , LIYANAGE M ,et al. Survey on multi-access edge computing for Internet of things realization[J]. IEEE Communications Surveys ＆ Tutorials, 2018,20(4): 2961-2991.
[10]	TALEB T , SAMDANIS K , MADA B ,et al. On multi-access edge computing:a survey of the emerging 5G network edge cloud architecture and orchestration[J]. IEEE Communications Surveys ＆ Tutorials, 2017,19(3): 1657-1681.
[11]	LEBRE A , PASTOR J , SIMONET A ,et al. Revising OpenStack to operate fog/edge computing infrastructures[C]// 2017 IEEE International Conference on Cloud Engineering (IC2E). Piscataway:IEEE Press, 2017: 138-148.
[12]	NIU Y P , LIU F M , LI Z P . Load balancing across microservices[C]// IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. Piscataway:IEEE Press, 2018: 198-206.
[13]	邬江兴 . 新型网络技术发展思考[J]. 中国科学:信息科学, 2018,48(8): 1102-1111.
	WU J X . Thoughts of the development of novel network technology[J]. SCIENTIA SINICA Informationis, 2018,48(8): 1102-1111.
[14]	朱建军, 方琰崴 . 面向服务的5G云原生核心网及关键技术研究[J]. 数字通信世界, 2018(2): 111.
	ZHU J J , FANG Y W . Research on service oriented 5G cloud native core network and its key technologies[J]. Digital Communication World, 2018(2): 111.
[15]	王全 . 云原生Cloud Native核心网方案及关键技术[J]. 中国新通信, 2018,20(9): 61-62.
	WANG Q . Cloud native core network scheme and key technologies[J]. China New Telecommunications, 2018,20(9): 61-62.
[16]	胡聪丛 . 无服务器计算的现状以及所面临的挑战[J]. 网络安全技术与应用, 2019(12): 84-85.
	HU C C . The current situation and challenges of serverless compu-ting[J]. Network Security Technology ＆ Application, 2019(12): 84-85.
[17]	HUNG Y H , WANG C Y . Fog micro service market:promoting fog computing using free market mechanism[C]// 2018 IEEE Wireless Communications and Networking Conference (WCNC). Piscataway:IEEE Press, 2018: 1-6.
[18]	YU R , KILARI V T , XUE G ,et al. Load balancing for interdependent IoT microservices[C]// IEEE Conference on Computer Communications. Piscataway:IEEE Press, 2019.
[19]	LI W B , LEMIEUX Y , GAO J ,et al. Service mesh:challenges,state of the art,and future research opportunities[C]// 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE). Pisca-taway:IEEE Press, 2019: 122-1225.
[20]	VILLARI M , CELESTI A , TRICOMI G ,et al. Deployment orchestration of microservices with geographical constraints for edge computing[C]// 2017 IEEE Symposium on Computers and Communications (ISCC). Piscataway:IEEE Press, 2017: 633-638.
[21]	WANG Y , ZHAO C , YANG S ,et al. MPCSM:microservice placement for edge-cloud collaborative smart manufacturing[J]. IEEE Transactions on Industrial Informatics, 2020.

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