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View all- Ferguson ALarrea JMarina M(2024)CoreKube: An Efficient, Autoscaling and Resilient Mobile Core SystemGetMobile: Mobile Computing and Communications10.1145/3665112.366511828:1(17-22)Online publication date: 13-May-2024
Modeling and Generating Control-Plane Traffic for Cellular Networks
Authors: 
Jiayi Meng, Jingqi Huang, Y. Charlie Hu, Yaron Koral, Xiaojun Lin, 
Muhammad Shahbaz, Abhigyan SharmaAuthors Info & Claims
Pages 660 - 677
Abstract
With 5G deployment gaining momentum, the control-plane traffic volume of cellular networks is escalating. Such rapid traffic growth motivates the need to study the mobile core network (MCN) control-plane design and performance optimization. Doing so requires realistic, large control-plane traffic traces in order to profile and debug the mobile network performance under real workload. However, large-scale control-plane traffic traces are not made available to the public by mobile operators due to business and privacy concerns. As such, it is critically important to develop accurate, scalable, versatile, and open-to-innovation control traffic generators, which in turn critically rely on an accurate traffic model for the control plane. Developing an accurate model of control-plane traffic faces several challenges: (1) how to capture the dependence among the control events generated by each User Equipment (UE), (2) how to model the inter-arrival time and sojourn time of control events of individual UEs, and (3) how to capture the diversity of control-plane traffic across UEs. We present a novel two-level hierarchical state-machine-based control-plane traffic model. We further show how our model can be easily adjusted from LTE to NextG networks (e.g., 5G) to support modeling future control-plane traffic. We experimentally validate that the proposed model can generate large realistic control-plane traffic traces. We have open-sourced our traffic generator to the public to foster MCN research.
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- Modeling and Generating Control-Plane Traffic for Cellular Networks
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October 2023
746 pages
ISBN:9798400703829
DOI:10.1145/3618257
- General Chairs:
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View all- Ferguson ALarrea JMarina M(2024)CoreKube: An Efficient, Autoscaling and Resilient Mobile Core SystemGetMobile: Mobile Computing and Communications10.1145/3665112.366511828:1(17-22)Online publication date: 13-May-2024
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