Toward Zero-Touch Management and Orchestration of Massive Deployment of Network Slices in 6G

Chergui, Hatim; Ksentini, Adlen; Blanco, Luis; Verikoukis, Christos

doi:10.1109/mwc.009.00366

Cited by 29 publications

(8 citation statements)

References 7 publications

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“…Several studies have addressed various aspects of network management, orchestration and integration of AI/ML techniques [7], [9], [10], [11], [12], [13], [14], [15], [16], [2]. Several European Commission-funded Horizon 2020 and other initiatives, such as FlexNGIA 1 (aims to design a novel internet architecture for the next-generation tactile internet that leverages recent technological advances in virtualization, network softwarization and AI) and projects such as 5G-MONARCH 2 (focusing on intra-slice and cross-slice controllers to enable reprogrammability and functional reconfiguration of slices), SliceNet 3 (focusing on cognitive mechanisms to achieve dynamic slice reconfiguration) integrate state-of-the-art techniques and standardization architectures from SDOs such as 3GPP [17], ETSI [18], [19], ITU-T (FG-ML5G group) to create new architectures or improve existing ones. The integration of AI/ML into the architectures of these SDOs is an area of active research [20], [21], [22].…”

Section: Related Work and Monb5g Vision A Related Workmentioning

confidence: 99%

“…RAN, transport network, core network and cloud) and the growth of edge computing, cloud computing and in-network computing, the management and orchestration process for mobile networks becomes increasingly complicated. Unfortunately, a centralized solution is also impractical in terms of scalability and sustainability to meet the needs of such emerging applications [2]. Therefore, it is imperative to reassess and revise the existing standardization solutions for network infrastructure management and orchestration to overcome the limitations by effectively leveraging the recent advances such as Artificial Intelligence (AI)/Machine Learning (ML), Software Defined Networks (SDN) or Network Function Virtualization (NFV) [3].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Approach for Scalable and Sustainable 6G Networks

Blanco,

Zeydan,

Barrachina-Muñoz

et al. 2024

IEEE Open J. Commun. Soc.

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Hierarchical, distributed, scalable and Artificial Intelligence (AI)-based management of a massive number of network slices in different domains with the goal of zero-touch management is a major challenge for 6G networks. In this paper, we first propose a new vision for distributed network management and orchestration based on existing standardization architectures. This vision aims to embed AI/Machine Learning (ML) into the AI/ML architectures of Standardization Development Organizations (SDOs) such as the 3rd Generation Partnership Project (3GPP), the European Telecommunications Standards Institute (ETSI) and the International Telecommunication Union (ITU). Our second contribution is a numerical comparison of the benefits of the proposed distributed management and orchestration approach in terms of energy savings through Federated Learning (FL). The experimental topology includes a sophisticated infrastructure with VR streaming clients and servers, a monitoring system (MS), core network elements, aggregation server for federated learning (FL) and analytics engines (AEs). The deployment uses Kubernetes (K8s) and a top orchestrator that works together with an AI/ML model tailored to the envisioned use case. Experimental studies emulating the demanding Virtual Reality (VR) video streaming have demonstrated the effectiveness of the MonB5G framework in optimizing resource management, reducing overhead and improving energy efficiency. In particular, when convergence is achieved, the monitoring overhead is reduced by more than 11 times compared to the centralised SLA-constrained algorithm, along with data-driven management systems. This led to a more than 10-fold improvement in energy efficiency. At the end of the paper, we also discuss experimental results, VR video streaming specific challenges, scalability considerations and lessons learned throughout the implementation.

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Section: Related Work and Monb5g Vision A Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Scalable and Sustainable 6G Networks

Blanco,

Zeydan,

Barrachina-Muñoz

et al. 2024

IEEE Open J. Commun. Soc.

Self Cite

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“…Zero-touch service management and intelligent networks can be a feasible solution for the intelligent and autonomous network orchestration and management techniques for 6G [129]. Different applications are considered in this technique but smart grid applications should still be well studied.…”

Section: Network Management and Orchestrationmentioning

confidence: 99%

Emerging 6G/B6G Wireless Communication for the Power Infrastructure in Smart Cities: Innovations, Challenges, and Future Perspectives

Al Amin,

Hong,

Bui

et al. 2023

Algorithms

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A well-functioning smart grid is an essential part of an efficient and uninterrupted power supply for the key enablers of smart cities. To effectively manage the operations of a smart grid, there is an essential requirement for a seamless wireless communication system that provides high data rates, reliability, flexibility, massive connectivity, low latency, security, and adaptability to changing needs. A contemporary review of the utilization of emerging 6G wireless communication for the major applications of smart grids, especially in terms of massive connectivity and monitoring, secured communication for operation and resource management, and time-critical operations, are presented in this paper. This article starts with the key enablers of the smart city, along with the necessity of the smart grid for the key enablers of it. The fundamentals of the smart city, smart grid, and 6G wireless communication are also introduced in this paper. Moreover, the motivations to integrate 6G wireless communication with the smart grid system are expressed in this article as well. The relevant literature overview, along with the novelty of this paper, is depicted to bridge the gap of the current research works. We describe the novel technologies of 6G wireless communication to effectively perform the considered smart grid applications. Novel technologies of 6G wireless communication have significantly improved the key performance indicators compared to the prior generation of the wireless communication system. A significant part of this article is the contemporary survey of the considered major applications of a smart grid that is served by 6G. In addition, the anticipated challenges and interesting future research pathways are also discussed explicitly in this article. This article serves as a valuable resource for understanding the potential of 6G wireless communication in advancing smart grid applications and addressing emerging challenges.

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“…Similarly, Chergui et al [14] built and evaluated a framework with AI-driven blocks for managing and orchestrating massive network slicing. The framework aimed to address scalability and zero-touch.…”

Section: Related Workmentioning

confidence: 99%

On Enhancing Network Slicing Life-Cycle Through an AI-Native Orchestration Architecture

Moreira

Martins

Carvalho

et al. 2023

Lecture Notes in Networks and Systems

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Legacy experimental network infrastructures can still host innovative services through novel network slicing orchestration architectures. Network slicing orchestration architectures available in state-of-the-art have building blocks that structurally change depending on the problem they are trying to solve. In these orchestrators, life-cycle functions of network slices experience advances on numerous fronts, such as combinatorial methods and Artificial Intelligence (AI). However, many of the state-of-the-art slicing architectures are not AI-native, making heterogeneity and the coexistence and use of machine learning paradigms for network slicing orchestration hard. Also, using AI in a non-native way makes network slice management a challenger and shallow. Hence, this paper proposes and evaluates a distributed AI-native slicing orchestration architecture that delivers machine learning capabilities in all life cycles of a network slice. Carried experiments suggest lower error using distributed machine learning models to predict Radio Access Network (RAN) resource consumption in slicing deployed over different target domains.

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Toward Zero-Touch Management and Orchestration of Massive Deployment of Network Slices in 6G

Cited by 29 publications

References 7 publications

A Novel Approach for Scalable and Sustainable 6G Networks

A Novel Approach for Scalable and Sustainable 6G Networks

Emerging 6G/B6G Wireless Communication for the Power Infrastructure in Smart Cities: Innovations, Challenges, and Future Perspectives

On Enhancing Network Slicing Life-Cycle Through an AI-Native Orchestration Architecture

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