近年來塞車的現象越來越頻繁，而V2X被視為一種能改善改善此情況的技術。為了實現低延遲V2X通訊，ETSI多接入邊緣計算(MEC)和ETSI網絡功能虛擬化(NFV)此兩項技術將被採用。NFV支持在行動網絡邊緣透過VNF的方式部署MEC，並支持NFV自主擴展為MEC服務動態分配資源。根據上述，我們設計並實現了一個基於NFV的MEC平台，利用客製化的V2X模組，為車輛提供低延遲的V2X服務。此外，我們設計並實現了一種根據車輛移動進行動態資源分配的NFV自主擴展機制，該機制可以預測下一時間段內V2X服務的資源需求，並在需要時提前觸發NFV自主擴展程序。實驗結果證明我們提出的平台可以提供低延遲的V2X服務，並為V2X服務分配合適的資源。

The traffic congestion has occurred more and more frequently during daily rush hours and holidays. To improve this situation, the vehicle-to-everything (V2X) is considered a promising technology. To enable low-latency V2X communications, two key technologies, the ETSI multi-access edge computing (MEC) and the ETSI network function virtualization (NFV) technology are adopted. The NFV enables the deployment of the MEC functionalities as virtual network functions (VNFs) at the edge of the mobile network and enables the dynamic resource allocation for the MEC services with the NFV auto scaling. In this paper, we design and implement an NFV-based edge platform which exploits customized V2X modules as VNFs to provide low-latency V2X services for vehicles. Then, we design and implement a vehicle mobility-driven NFV auto scaling mechanism which forecasts the resource requirements of V2X services in the next time interval and triggers the NFV auto scaling in advance if needed. The experiment results show that our proposed platform can provide low-latency V2X services as well as allocating suitable resources to V2X services.

[1] ETSI, “Multi-access edge computing (mec); framework and reference architecture (etsi gs mec 003 v2.1.1),” Group Specification (GS) 003, ETSI Industry Specification Group (ISG), Jan. 2019.
[2] ETSI, “Network functions virtualisation (nfv); architecture framework (etsi gs nfv 002 v1.1.1),” Group Specification (GS) 002, ETSI Industry Specification Group (ISG), Oct. 2013.
[3] J. Lee, Y. Kim, Y. Kwak, J. Zhang, A. Papasakellariou, T. Novlan, C. Sun, and Y. Li, “Lteadvanced in 3gpp rel -13/14: an evolution toward 5g,” IEEE Communications Magazine, vol. 54, no. 3, pp. 36–42, 2016.
[4] 3GPP, “Study on enhancement of 3gpp support for 5g v2x services (v16.2.0, release 16),” Technical Report (TR) 22.886, 3rd Generation Partnership Project (3GPP), Dec. 2018.
[5] L. Hobert, A. Festag, I. Llatser, L. Altomare, F. Visintainer, and A. Kovacs, “Enhancements of v2x communication in support of cooperative autonomous driving,” IEEE Communications Magazine, vol. 53, no. 12, pp. 64–70, 2015.
[6] M. Boban, A. Kousaridas, K. Manolakis, J. Eichinger, and W. Xu, “Connected roads of the future: Use cases, requirements, and design considerations for vehicle-to-everything communications,” IEEE Vehicular Technology Magazine, vol. 13, no. 3, pp. 110–123, 2018.
[7] 5GPPP, “5g automotive vision,” white paper, 2015.
[8] M. Emara, M. C. Filippou, and D. Sabella, “Mec-assisted end-to-end latency evaluations for c-v2x communications,” in 2018 European Conference on Networks and Communications (EuCNC), pp. 1–9, 2018.
[9] H. Zhang, Z. Wang, and K. Liu, “V2x offloading and resource allocation in sdn-assisted mec-based vehicular networks,” China Communications, vol. 17, no. 5, pp. 266–283, 2020.
[10] N. Raza, S. Jabbar, J. Han, and K. Han, “Social vehicle-to-everything (v2x) communication model for intelligent transportation systems based on 5g scenario,” in Proceedings of the 2nd International Conference on Future Networks and Distributed Systems, ICFNDS ’18, (New York, NY, USA), Association for Computing Machinery, 2018.
[11] S. Herker, X. An, W. Kiess, S. Beker, and A. Kirstaedter, “Data-center architecture impacts on virtualized network functions service chain embedding with high availability requirements,” in 2015 IEEE Globecom Workshops (GC Wkshps), pp. 1–7, 2015.
[12] Amazon, “Amazon Web Services - Auto-scaling.” https://aws.amazon.com/tw/ autoscaling/. [Online; accessed 18-April-2017].
[13] A. Boubendir, E. Bertin, and N. Simoni, “On-demand, dynamic and at-the-edge vnf deployment model application to web real-time communications,” in 2016 12th International Conference on Network and Service Management (CNSM), pp. 318–323, 2016.
[14] S. Li, Z. Guo, G. Shou, Y. Hu, and H. Li, “Qoe analysis of nfv-based mobile edge computing video application,” in 2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), pp. 411–415, 2016.
[15] G. A. Carella, M. Pauls, T. Magedanz, M. Cilloni, P. Bellavista, and L. Foschini, “Prototyping nfv-based multi-access edge computing in 5g ready networks with open baton,” in 2017 IEEE Conference on Network Softwarization (NetSoft), pp. 1–4, 2017.
[16] F. Giust, V. Sciancalepore, D. Sabella, M. C. Filippou, S. Mangiante, W. Featherstone, and D. Munaretto, “Multi-access edge computing: The driver behind the wheel of 5gconnected cars,” IEEE Communications Standards Magazine, vol. 2, no. 3, pp. 66–73, 2018.
[17] B. Yang, W. K. Chai, Z. Xu, K. V. Katsaros, and G. Pavlou, “Cost-efficient nfv-enabled mobile edge-cloud for low latency mobile applications,” IEEE Transactions on Network and Service Management, vol. 15, no. 1, pp. 475–488, 2018.
[18] T. Subramanya and R. Riggio, “Machine learning-driven scaling and placement of virtual network functions at the network edges,” in 2019 IEEE Conference on Network Softwarization (NetSoft), pp. 414–422, 2019.
[19] I. Sarrigiannis, K. Ramantas, E. Kartsakli, P. Mekikis, A. Antonopoulos, and C. Verikoukis,“Online vnf lifecycle management in an mec-enabled 5g iot architecture,” IEEE Internet of Things Journal, vol. 7, no. 5, pp. 4183–4194, 2020.
[20] H. Huang and S. Guo, “Proactive failure recovery for nfv in distributed edge computing,” IEEE Communications Magazine, vol. 57, no. 5, pp. 131–137, 2019.
[21] H. Yu, S. Yang, Z. Wu, and X. Ma, “Vehicle trajectory reconstruction from automatic license plate reader data,” International Journal of Distributed Sensor Networks, vol. 14, p. 155014771875563, 02 2018.
[22] M. Nasir, M. A. Kalam, B. Masum, and R. Md. Noor, “Reduction of fuel consumption and exhaust pollutant using intelligent transport system,” The Scientific World Journal, 04 2014.
[23] L. Ma, D. Zhou, and W. Han, “A study on the impact coefficient of traffic flows on a large cable-stayed bridge in a windy environment,” Shock and Vibration, vol. 2014, 11 2014.
[24] S. Waidande, “A literature survey on scaling approaches for vnf in nfv monitoring,” 2018.
[25] H. Khalili, A. Papageorgiou, S. Siddiqui, C. Colman-Meixner, G. Carrozzo, R. Nejabati, and D. Simeonidou, “Network slicing-aware nfv orchestration for 5g service platforms,” in 2019 European Conference on Networks and Communications (EuCNC), pp. 25–30, 2019.
[26] F.-J. R. S. (Telefónica), “Introducing Open Source MANO.” https://osm.etsi.org/wikipub/images/5/5a/OSM_Introduction_Francisco.pdf. [Online].
[27] OSM, “Setup of Virtual Infrastructure Managers (VIMs).” https://osm.etsi.org/docs/user-guide/04-vim-setup.html. [Online].
[28] OpenStack, “Accelerating NFV Delivery with Open-Stack.” https://object-storage-ca-ymq-1.vexxhost.net/swift/v1/6e4619c416ff4bd19e1c087f27a43eea/www-assets-prod/telecoms-and-nfv/OpenStack-Foundation-NFV-Report.pdf. [Online].
[29] RedHat, “OpenStack, packaged for and tested on CentOS..” https://www.rdoproject.org//. [Online].
[30] OSM, “OSM Usage.” https://osm.etsi.org/docs/user-guide/05-osm-usage.html. [Online].
[31] H. C. Government, “Urban Planning Division Announcement.” http://www.v523.tw/upload/fileUrl/2015-11/05/616d1834-07f1-4ac4-865d-60a2f7ab5e8b.pdf. [Online].
[32] S. Kekki, W. Featherstone, Y. Fang, P. Kuure, A. Li, A. Ranjan, D. Purkayastha, F. Jiangping, D. Frydman, G. Verin, K.-W. Wen, K. Kim, R. Arora, A. Odgers, L. M. Contreras, and S. Scarpina, “Mec in 5g networks,” White Paper 28, ETSI), June 2018.
[33] OpenSignal, “Taiwan Mobile Network Experience Report.” https://www.opensignal.com/reports/2019/06/taiwan/mobile-network-experience, June 2018. [Online].
[34] Z. Amjad, A. Sikora, B. Hilt, and J. Lauffenburger, “Low latency v2x applications and network requirements: Performance evaluation,” in 2018 IEEE Intelligent Vehicles Symposium (IV), pp. 220–225, 2018.