Co-located with IEEE 102nd Vehicular Technology Conference: (VTC2025-Fall)
Scope
As networks and services grow increasingly complex and dynamic, the need for efficient and intelligent management solutions becomes paramount. Automated Machine Learning (AutoML) has emerged as a transformative technology with the potential to revolutionize network and service management by enabling "zero-touch" operations. AutoML leverages Artificial Intelligence (AI) and Machine Learning (ML) to automate the design, deployment, and optimization of network and service configurations, leading to enhanced performance, reduced downtime, and improved user experiences. The primary focus is on the application of AutoML in the context of 5GB, 6G, and other advanced technologies. This workshop encompasses a broad spectrum of topics, including the use of AutoML to automate the design, deployment, and optimization of network and service configurations, resulting in enhanced performance, reduced downtime, and improved user experiences. It explores the concept of zero-touch operations, delving into the benefits and real-world implementations of this approach. Integrating AutoML into the 5G and 6G landscape, security implications, and service orchestration are key discussion areas. Additionally, the workshop addresses the challenges and opportunities of AutoML in cross-domain, multi-vendor environments. It encourages the sharing of best practices, case studies, and future research directions to advance the field.
Topics of Interest:
We invite researchers and practitioners to submit their latest research and innovative solutions in the area of Automated Machine Learning (AutoML) for Zero-touch Network and Service Management. Topics of interest include, but are not limited to:
Zero-touch provisioning and deployment of network services
Self-healing and self-optimizing networks
Predictive maintenance and fault detection
Real-time network performance monitoring
Network automation and orchestration
Data-driven approaches for network and service management
AI-driven analytics and insights for network operations
Security and reliability in AutoML-enabled networks
Cross-domain and Cross-layer Integration
Edge computing and AutoML
Sustainability and energy efficiency
AI in Network Slicing
Federated learning and reinforcement learning for intelligent communications
Intelligent network slicing techniques
RAN configuration optimization
Case studies and real-world applications of AutoML in network management
Paper Submission
Submission requirements: 5-page paper (without overlength charge) and up to 2 additional pages are allowed with the purchase of additional page charges in the amount of $100 USD per additional page at the time of registration and final paper submission.
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For more information, please see the IEEE VTC2025-Fall official website: https://events.vtsociety.org/vtc2025-fall/conference-sessions/workshops-currently-available/
IMPORTANT DATES
Paper submission deadline Extended: 24 May 2025
Acceptance notification: 15 July 2025
Final paper submission deadline: 29 July 2025