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Zero Touch Network and Service Management (ZSM) refers to the concept of automating network and service management tasks without requiring manual intervention. It aims to minimize human involvement in network operations, configuration, provisioning, and troubleshooting, thereby increasing operational efficiency, reducing costs, and improving service quality. ZSM relies on various technologies and approaches to achieve these goals. Some key components and techniques involved in ZSM include Orchestration and Automation, Software-Defined Networking (SDN), Network Function Virtualization (NFV), etc.

On the other side, Advanced Artificial Intelligence (AAI) algorithms, including Generative AI, Large Language Models, Attention mechanisms, transformers, are expected to play a crucial role in enabling ZSM by automating and optimizing various aspects of network and service operations. AAI can be applied for:

1. Network Monitoring and Management: AAI-powered algorithms can analyze network telemetry data in real-time to detect anomalies, predict issues, and identify performance bottlenecks. This enables proactive monitoring, fault detection, and automated network management without human intervention.
2. Intelligent Service Orchestration: AAI can optimize service provisioning and orchestration processes by considering factors like service requirements, network conditions, and resource availability. AAI algorithms can facilitate automatic allocate resources, optimize routing, and dynamically adjust service configurations to meet service-level objectives.
3. Security and Threat Detection: AAI techniques can enhance network security by analyzing network traffic patterns, identifying anomalies, and detecting potential security threats in real-time. This helps in automated threat detection, response, and mitigation, ensuring the integrity and security of network and service operations.
4. Network Optimization and Planning: AAI techniques can optimize network infrastructure design and planning by considering factors like traffic patterns, service requirements, and resource availability. AAI algorithms can generate optimal network designs, recommend network upgrades, and optimize resource allocation to meet evolving service demands.

Although AAI can help in reducing manual intervention, improving service quality, enhancing network performance, and enabling seamless operations. AAI-based models are becoming complex that is difficult to understand the inner working of such models, especially by non-expert users. Consequently, AAI models are deployed as black-boxes. In addition, decisions made by such models are provided to user, without any explanations or interpretations of how and why these decisions are made. Therefore, the corresponding users can neither understand and trust these decisions, nor optimize them, based on AAI outputs. To overcome these limits, Explainable Artificial Intelligence (XAI) is also an emerging paradigm that opts to overcome these limitations.

This Special Issue (SI) intends to report on recent advances and on-going studies on the use of ZSM networks and AAI techniques for network monitoring and management, intelligent service orchestration, security and threat detection, network optimization and planning. Possible topics include, but are not limited to:

• AAI and XAI for transparency and interpretability of AI-empowered models in ZSM networks.
• AAI and XAI for anomaly detection in ZSM networks.
• AAI and XAI for predictive maintenance in ZSM networks.
• AAI and XAI for root cause analysis in ZSM networks.
• AAI and XAI for incident resolution in ZSM networks.
• AAI and XAI for continuous learning in ZSM networks.
• AAI and XAI for human-AI collaboration in ZSM networks.
• AAI and XAI for open-RAN in ZSM networks.
• AAI and XAI for network optimization and planning in ZSM networks.
• AAI and XAI for intelligent service orchestration in ZSM networks.
• Security of AAI and XAI in ZSM networks.
• AAI and XAI for intelligent network adaptation and recovery in ZSM network.
• AAI and XAI for resource allocation in ZSM network.
• AAI for Network Monitoring, Management and Optimization.
• AAI for Intelligent Service Orchestration.
• AAI for Security and Threat Detection.

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Manuscript Submission Guidelines. Please, check these guidelines carefully before submitting since submissions not complying with them will be administratively rejected without review.

Solicited and invited papers shall undergo the standard IEEE peer review process. After initial screening, the paper will immediately go to the review process. Prospective authors should submit their manuscripts following the IEEE Communication Magazine guidelines. Authors should submit a PDF version of their complete manuscript to IEEE Submission Portal.

Important Dates

Manuscript Submission Deadline: 15 April 2025 (Deadline Extended)
Initial Decision Date: 5 May 2025
Revised Manuscript Due: 20 June 2025
Final Decision Date: 30 July 2025
Final Manuscript Due: 30 August 2025
Publication Date: December 2025

Guest Editors

Bouziane Brik (Lead Guest Editor)
Sharjah University, UAE

Miloud Begaa
Université du Québec à Trois-Rivières, Canada

Mohamed Younis
University of Maryland Baltimore County, USA

Marco Di Renzo
Paris-Saclay University, France