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Intent-Based Network Slice Life Cycle Management
Khizar Abbas,Talha Ahmed Khan,Afaq Muhammad,Wang-Cheol Song 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.2
5G networks have to accommodate a diverse set of services with different performance, latency, bandwidth, and reliability requirements. It is not possible to handle multi-services needs with legacy cellular networks due to the same physical infrastructure. The programmable and virtualized nature of the 5G network makes it possible to manage these multi-services by providing different resources to each service. Network slicing is a promising solution to support the multi-services environment where the same physical network is partitioned into isolated multiple logical networks. This research paper has proposed an end-to-end (e2e) network slicing through an intent-based network (IBN) approach. Our system can manage the life cycle of the network slice in an automated fashion. It can also monitor, update, and manage the slices by using deep learning.
Network Data Analytics Function for Network Slice Lifecycle Management: a closed-loop approach
Khizar Abbas,Talha Ahmed Khan,Muhammad Afaq,Wang-Cheol Song 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
Networks slicing in 5G network enables the network operators to accommodate the different quality of service (QoS) to their customers. The orchestration and management of the end-to-end (e2e) network slicing is a critical task. So, for that, we have designed a closed-loop Intent-based Networking (IBN) platform, which ensures the commissioning, activation, run-time monitoring, and decommissioning of the network slices automatically. Moreover, we have integrated the newly proposed 3GPP network data analytics function (NWDAF) with the IBN platform for efficient e2e network slice lifecycle management. By implemented different Machine Learning (ML) models in the NWDAF function, we can predict the slice load, user mobility, traffic forecasts, and anomaly detection from the network slices.
IBNSlicing: Intent-Based Network Slicing Framework for 5G Networks using Deep Learning
Khizar Abbas,Muhammad Afaq,Talha Ahmed Khan,Asif Mehmood,Wang-Cheol Song 한국통신학회 2020 한국통신학회 APNOMS Vol.2020 No.09
Network slicing is an important pillar of 5G networks that empowers the network operators to provide the different quality of services (QoS) to the users. It enables network operators to split the physical network into multiple logical networks to meet different QoS requirements. In this research paper, we have designed an intent-based network slicing framework that can slice and manage the core network and radio access network (RAN) resources efficiently. It is an automated system, where users just needs to provide higher-level information in the form of intents/contracts for a network slice, and in return our system deploys and configures the requested resources. Moreover, a deep learning model Generative Adversarial Neural Network (GAN) has been used for the management of network resources. Several tests have been performed by creating three slices with our system, which shows better performance in terms of bandwidth and latency.
IBN-based E2E Service Orchestration on Top of KOREN
Khan Talha Ahmed,Khizar Abbas,Afaq Muhammad,Wang-Cheol Song 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6
The increasing number of services impacted in the rise of complexity for E2E service orchestration. The newer network requirements of bandwidth achievement and QoS requirements have forced the researcher towards innovative design of underlying networks. This work proposes an IBN-based E2E service orchestration which will automate the process of service provisioning and its dynamic management. The proposed system will ensure the service assurance while keeping the requested context of the service. In addition, the IBN platform will enable orchestration of service for UAV (Unmanned Arial Vehicles) over several underlying platforms. It also considers the orchestration of service over multiple domains and utilizes FlexRAN and OSM (OpsourceMANO) as RAN and Core orchestrators. In addition, it is based on KOREN Transport infrastructure to interconnect multiple domains.
A Machine-Learning-Driven Multi-Objective Optimization for IBN-Based Orchestration
Khan Talha Ahmed,Khizar Abbas,Afaq Muhammad,Wang-Cheol Song 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
Modern networks are aimed at offering state-of-the-art services for their users. However, each impending service requires a distinct KPI (Key Performance Indicators) and is distributed over an extensive infrastructure. Thus, requiring a complex service orchestration procedure having explicit policies throughout the low-level network infrastructure. However, the achievement of such policies at the low level over globally distributed, multi-vendor infrastructure has multi-dimensional complexity. Also, it is very challenging to perform dynamic assessment and update procedure at low-level infrastructure using traditional approaches. Hence, this manuscript, on one end, considers resolving multi-dimensional KPI achievement through Machine-Learning assisted multi-objective optimization. On the other hand, it uses the IBN approach that enables high-level service definition, and it automates the policy deployment on the low-level infrastructure.