基于在线双向拍卖的虚拟网络切片资源调度机制

陈前斌; 施颖洁; 杨希希; 唐伦

doi:10.11999/JEIT170902

基于在线双向拍卖的虚拟网络切片资源调度机制

doi: 10.11999/JEIT170902

(重庆邮电大学移动通信技术重点实验室重庆 400065)

基金项目:

国家自然科学基金(61571073)

详细信息

作者简介:
陈前斌：男，1967年生，教授，博士生导师，主要研究方向为个人通信、下一代移动通信网络、异构蜂窝网络等. 施颖洁：女，1993年生，硕士生，研究方向为虚拟资源分配. 杨希希：女，1992年生，硕士生，研究方向为网络虚拟化. 唐伦：男，1973年生，教授，研究方向为新一代无线通信网络、异构蜂窝网络、软件定义无线网络等.

中图分类号: TN929.5
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出版历程
- 收稿日期: 2017-09-22
- 修回日期: 2018-03-23
- 刊出日期: 2018-07-19

Resource Scheduling Mechanism for Virtual Network Slice Based on Online Double Auction

CHEN Qianbin SHI Yingjie YANG Xixi TANG Lun

Funds:

The National Natural Science Foundation of China (61571073)

摘要

摘要: 为解决 5G网络切片间资源分配的问题，该文提出一种基于在线双向拍卖 (ODA)的资源调度机制。该机制首先针对不同的业务需求和业务收益确定网络切片的优先级和单位资源报价；其次明确最大化网络收益的目标建立线下单向拍卖模型；进一步，考虑资源的动态分配和回收利用，提出价格更新算法实时更新资源价格；最后，综合线下单向拍卖机制和价格动态变化机制建立在线双向拍卖模型，为切片动态分配资源。仿真结果表明，该机制在提高网络收益的同时可以保证各切片用户的QoS需求。
- 5G虚拟网络切片 /
- 资源分配 /
- 在线双向拍卖 /
- 切片优先级
Abstract: In order to solve the problem of resource allocation between 5G virtual network slice, a resource scheduling mechanism based on Online Double Auction (ODA) is proposed. Firstly, the priority of network slices and unit resource quotes are determined according to different traffic needs and traffic benefits. Then, to maximize the network revenue, an offline single auction model is established. Further, based on the resources dynamic allocation and recycling, the price-updating algorithm is proposed to update the resource price in real time. Finally, the offline single auction mechanism and the price update mechanism are combined to establish ODA model and allocate resources dynamically for the network slices. The simulation results show that the proposed mechanism can improve network revenue and guarantee the QoS requirement of each slice user.
- 5G virtual network slices、Resource allocation、Online Double Auction (ODA)、Slice priority /

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参考文献(12)

N ALLIANCE. NGMN 5G White Paper[OL]. https:// www.ngmn.org/fileadmin/ngmn/content/downloads/Technical/2015/NGMN_5G_White_Paper_V1_0.pdf, 2015

[2] WAN NSFWA, ZHANG X, and NAKHAI M R. Sparse beamforming for real-time resource management and energy trading in Green C-RAN[J]. IEEE Transactions on Smart Grid, 2017, 8(4): 2022-2031. doi: 10.1109/TSG.2016. 2601718.

[3] CHEN J L, MA Y W, KUO H Y, et al. Software-defined network virtualization platform for enterprise network resource management[J]. IEEE Transactions on Emerging Topics in Computing, 2016, 4(2): 179-186. doi: 10.1109/ TETC.2015.2478757.

[4] PINGZHI F, JING Z, and CHIH-LIN I. 5G high mobility wireless communications: challenges and solutions[J]. China Communications, 2017, 13(Suppl.2): 1-13. doi: 10.1109/CC.2016.7833456.

[5] WANG X, CHE H, LI K, et al. An intelligent economic approach for dynamic resource allocation in cloud services[J]. IEEE Transactions on Cloud Computing, 2015, 3(3): 275-289. doi: 10.1109/TCC.2015.2415776.

[6] LOLOS K, KONSTANTINOU I, KANTERE V, et al. Adaptive state space partitioning of markov decision processes for elastic resource management[C]. 2017 IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, USA, 2017: 191-194. doi: 10.1109/ICDE.2017.72.

[7] YAN Y, SI P, and ZHANG Y. B-CaB: Optimizing the SP,s bidding for cache and band resources in virtualized wireless networks[C]. International Conference on Network and Information Systems for Computers (ICNISC), Wuhan, China, 2016: 17-22. doi: 10.1109/ICNISC.2016.014.

[8] MASHAYEKHY L, NEJAD M M, and GROSU D. Physical machine resource management in clouds: A mechanism design approach[J]. IEEE Transactions on Cloud Computing, 2015, 3(3): 247-260. doi: 10.1109/TCC.2014.2369419.

[9] SEMASINGHE P, MAGHSUDI S, and HOSSAIN E. Game theoretic mechanisms for resource management in massive wireless IoT systems[J]. IEEE Communications Magazine, 2017, 55(2): 121-127. doi: 10.1109/MCOM.2017.1600568CM.

[10] KAMEL M I, LONG B L, et al. LTE wireless network virtualization: dynamic slicing via flexible scheduling[C]. IEEE Vehicular Technology Conference, Vancouver, Canada. 2014: 1-5. doi: 10.1109/VTCFall.2014.6966044.

[11] SCIANCALEPORE V, SAMDANIS K, COSTA-PEREZ X, et al. Mobile traffic forecasting for maximizing 5G network slicing resource utilization[C]. IEEE Conference on Computer Communications, Atlanta, USA, 2017: 1-9. doi: 10.1109/INF OCOM.2017.8057230.

[12] ZHU K and HOSSAIN E. Virtualization of 5G cellular networks as a hierarchical combinatorial auction[J]. IEEE Transactions on Mobile Computing, 2016, 15(10): 2640-2654. doi: 10.1109/TMC.2015.2506578.

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