ABSTRACT
Next-generation mobile core networks are being designed to support a variety of latency sensitive applications based on emerging virtual, augmented or mixed reality technologies. A cloud-native approach for 5G core has been proposed to meet the diverse service requirements of NextG while reducing both CAPEX and OPEX. In this context, microservice architecture for network function virtualization is generally considered to be suitable for meeting NextG service requirements. Despite many advantages, the cloud-native core raises new challenges in the design of NextG systems for latency critical applications. An approach to achieving diverse QoS requirements is proposed in this paper. Specifically, the design is based on an orchestrator called the MEC-Intelligent Agent (MEC-IA) which enables dynamic compute resource distribution and network slice assignment in the core for improved QoS. The MEC-IA framework realizes resource management by intelligently assigning UEs to the access and mobility management function (AMF) while also performing slice provisioning. Simulation results are presented for the proposed MEC-IA framework showing the median control plane delay reduced by a factor of 1.67 ×. Further, robustness of the system improves significantly, reflecting a better overall user experience since the percentage connection dropped at 3 × traffic volume reduces by 1.5 × and slices assignment increases by 1.4 × across all slices, even when the traffic arrival is skewed.
- 2022. Basic performance equation. http://www0.cs.ucl.ac.uk/teaching/B261/Slides/lecture2/tsld015.htm.Google Scholar
- Imad Alawe, Yassine Hadjadj-Aoul, Adlen Ksentini, Philippe Bertin, and Davy Darche. 2018. On the scalability of 5g core network: the amf case. In 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 1–6.Google ScholarDigital Library
- PC Amogh, Goutham Veeramachaneni, Anil Kumar Rangisetti, Bheemarjuna Reddy Tamma, and A Antony Franklin. 2017. A cloud native solution for dynamic auto scaling of MME in LTE. In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 1–7.Google ScholarDigital Library
- Xueli An, Fabio Pianese, Indra Widjaja, and Utku Günay Acer. 2012. DMME: A distributed LTE mobility management entity. Bell Labs Technical Journal 17, 2 (2012), 97–120.Google ScholarDigital Library
- Ashutosh Balakrishnan, Swades De, and Li-Chun Wang. 2020. Traffic skewness-aware performance analysis of dual-powered green cellular networks. In GLOBECOM 2020-2020 IEEE Global Communications Conference. IEEE, 1–6.Google ScholarDigital Library
- Arijit Banerjee, Rajesh Mahindra, Karthik Sundaresan, Sneha Kasera, Kobus Van der Merwe, and Sampath Rangarajan. 2015. Scaling the LTE control-plane for future mobile access. In Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies. 1–13.Google ScholarDigital Library
- Gabrial Brown. 2017. Service-based architecture for 5G core networks. Huawei White Paper 1(2017).Google Scholar
- Shihabur Rahman Chowdhury, Mohammad A Salahuddin, Noura Limam, and Raouf Boutaba. 2019. Re-architecting NFV ecosystem with microservices: State of the art and research challenges. IEEE Network 33, 3 (2019), 168–176.Google ScholarCross Ref
- J Clement. 2019. Global mobile data traffic 2017-2022. Statista, Available: https://www. statista. com/statistics/271405/global-mobile-datatraffic-forecast/(Accessed September 2022) (2019).Google Scholar
- Qiang Duan, Shangguang Wang, and Nirwan Ansari. 2020. Convergence of networking and cloud/edge computing: Status, challenges, and opportunities. IEEE Network 34, 6 (2020), 148–155.Google ScholarDigital Library
- Endri Goshi, Michael Jarschel, Rastin Pries, Mu He, and Wolfgang Kellerer. 2021. Investigating inter-nf dependencies in cloud-native 5g core networks. In 2021 17th International Conference on Network and Service Management (CNSM). IEEE, 370–374.Google ScholarCross Ref
- Adlen Ksentini, Tarik Taleb, and Khaled B Letaif. 2015. QoE-based flow admission control in small cell networks. IEEE Transactions on Wireless Communications 15, 4(2015), 2474–2483.Google ScholarDigital Library
- Dongheon Lee, Sheng Zhou, Xiaofeng Zhong, Zhisheng Niu, Xuan Zhou, and Honggang Zhang. 2014. Spatial modeling of the traffic density in cellular networks. IEEE Wireless Communications 21, 1 (2014), 80–88.Google ScholarCross Ref
- Jayakumar Loganathan, S Janakiraman, and TP Latchoumi. 2017. A novel architecture for next generation cellular network using opportunistic spectrum access scheme. Journal of Advanced Research in Dynamical and Control Systems,(12) (2017), 1388–1400.Google Scholar
- Bipin B Nandi, Ansuman Banerjee, Sasthi C Ghosh, and Nilanjan Banerjee. 2013. Dynamic SLA based elastic cloud service management: A SaaS perspective. In 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013). IEEE, 60–67.Google Scholar
- Matteo Pozza, Patrick K Nicholson, Diego F Lugones, Ashwin Rao, Hannu Flinck, and Sasu Tarkoma. 2020. On reconfiguring 5G network slices. IEEE Journal on Selected Areas in Communications 38, 7(2020), 1542–1554.Google ScholarCross Ref
- Rajaneesh Shetty, Anil Jangam, and Ananya Simlai. 2021. Intelligent Strategies for Overload Detection & Handling for 5G Network. In 2021 IEEE 4th 5G World Forum (5GWF). IEEE, 135–140.Google Scholar
- Lucas BD Silveira, Henrique C de Resende, Cristiano B Both, Johann M Marquez-Barja, Bruno Silvestre, and Kleber V Cardoso. 2022. Tutorial on communication between access networks and the 5G core. Computer Networks (2022), 109301.Google Scholar
- Gaurav Somani, Prateek Khandelwal, and Kapil Phatnani. 2012. VUPIC: Virtual machine usage based placement in IaaS cloud. arXiv preprint arXiv:1212.0085(2012).Google Scholar
- Yusuke Takano, Ashiq Khan, Motoshi Tamura, Shigeru Iwashina, and Takashi Shimizu. 2014. Virtualization-based scaling methods for stateful cellular network nodes using elastic core architecture. In 2014 IEEE 6th International Conference on Cloud Computing Technology and Science. IEEE, 204–209.Google ScholarDigital Library
- Jinjun Xiong and Huamin Chen. 2020. Challenges for building a cloud native scalable and trustable multi-tenant AIoT platform. In 2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD). IEEE, 1–8.Google ScholarDigital Library
Index Terms
Invited Paper: Intelligent Agent Support for Achieving Low Latency in Cloud-Native NextG Mobile Core Networks
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