Resource Allocation with Admission Control for GBR and Delay QoS in 5G Network Slices

Buyakar, Tulja Vamshi Kiran and Agarwal, Harsh and Tamma, Bheemarjuna Reddy and Franklin, A Antony (2020) Resource Allocation with Admission Control for GBR and Delay QoS in 5G Network Slices. In: 2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020, 7 January 2020 - 11 January 2020.

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Abstract

Network slicing is an integral part of 5G, which supports next-generation wireless applications over a shared network infrastructure. It paves the way to leverage the full potential of 5G by increasing the efficiencies through differentiation and faster time-to-market. In this work, we propose a Mobile Virtual Network Operator (MVNO) Slice Resource Allocation Architecture (MSRAA) for supporting different network slices in the 5G data plane. MSRAA supports QoS parameters, including Guaranteed Bit Rate (GBR) and Maximum Delay Budget. Using long short-term memory (LSTM) neural networks, we predict network slices bandwidth requirements for efficiently allocating the resources. To reduce revenue loss to the network operators due to forecasting errors, the proposed Bandwidth Admission Control (BAC) algorithm, reallocates resources from lower priority slices (e.g., best-effort users) to higher priority slices (e.g., guaranteed service users). Using Mondrain Random Forests in our Delay Admission Control (DAC) algorithm, we predict the end-to-end delay and admit flows into slices that can satisfy delay requirements. We implement MSRAA on our advanced 5G Core testbed and evaluate User Service Request (USR) acceptances and do a complete cost-benefit analysis of our architecture. We show that for eMBB-GBR and eMBB-Non-GBR slices, our algorithm is showing a significant reduction in costs.

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IITH Creators:
IITH CreatorsORCiD
Buyakar, Tulja Vamshi KiranUNSPECIFIED
Agarwal, HarshUNSPECIFIED
Tamma, Bheemarjuna ReddyUNSPECIFIED
Franklin, AntonyUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bandwidth; Budget control; Computational complexity; Cost benefit analysis; Decision trees; Economics; Forecasting; Long short-term memory; Network architecture; Quality of service; Queueing networks; Random forests; Resource allocation
Subjects: Computer science
Divisions: Department of Computer Science & Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 20 Jul 2021 05:21
Last Modified: 09 Mar 2022 10:40
URI: http://raiith.iith.ac.in/id/eprint/8450
Publisher URL: http://doi.org/10.1109/COMSNETS48256.2020.9027310
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