March 2026 - RACI-list - mailman.ripe.net

CfP - IEEE MNC Special Session on AI-Native and Data-Driven Management for Next-Generation Networks
by GIOVANNI STANCO 30 Mar '26

30 Mar '26

================================================================================ CALL FOR PAPERS Special Session: AI-Native and Data-Driven Management for Next-Generation Networks Part of the 2026 IEEE International Symposium on Measurement in Networking and Communications Napoli, Italy - July 13-16, 2026 https://mnc2026.ieee-ims.org/program/special-sessions#session-1-1 ================================================================================ We invite the submission of original research contributions to the Special Session on AI-Native and Data-Driven Management for Next-Generation Networks, organized within the framework of the 2026 IEEE International Symposium on Measurement in Networking and Communications, held in Napoli, Italy, July 13-16, 2026. AI-Native and Data-Driven Management is important and promising for Measurement in Networking since it will enable automatic optimization and network management. Over the years, Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly pervasive in networking and communications, playing a key role in the development, deployment, and management of next-generation networks. Current research trends show how AI can enhance 5G networks at at the RAN, Edge, and Core layers, using measured data coming from multiple entities. While AI adoption in 5G has been an evolving process, 6G is envisioned as truly AI-native. The next generation of mobile networks will embed "connected intelligence" throughout its architecture, leveraging AI for network design, optimization, and autonomous operation. In 6G, AI will not only enhance network performance but also enable and support AI-driven services running seamlessly across the entire network from the user equipment to the network core. Through this AI-native framework, the network will be capable of analyzing real-time data to jointly orchestrate functions such as scheduling, network slicing, and strategic planning. AI technologies in fact, expand new potential in the optimization of the full end-to-end chain of the physical layer, from the transmitter to the receiver, enabling self-optimization by combining advanced sensing and data collection also introducing the capability to consider network metrics, such as current spectrum, power conditions, and number of connections, evolving because of signal reflections off buildings and weather patterns for constant re-optimization. Monitoring of real-time environmental and contextual data is a promising enabler for ML-based air interface optimization, leading to more efficient spectrum use and reduced latency. Not only, nowadays, AI is now further enhanced and made more interpretable through XAI methodologies, which allow us to better understand how the algorithms operate and which features are most relevant for predictions. Topics of interest include, but are not limited to: * Measurements for 6G, beyond-5G, and next-generation communications * Trustworthy AI and explainable measurement approaches * AI/ML-driven network measurement and diagnostics * Software-defined and virtualized network measurement * Big Data analytics for network traffic, QoS, and QoE evaluation * Security, privacy, and reliability network measurements in 5G and 6G ***Timeline*** Paper registration: April 6, 2026 Initial manuscript deadline: April 6, 2026 ***Manuscript submission information*** Authors are invited to submit a Full Paper (4-6 pages) reporting original research of a theoretical or applied nature using the online submission system, EDAS. EDAS Submission Link: https://edas.info/N34568 Further information available: https://mnc2026.ieee-ims.org/author-information ***Special Session Chairs*** Prof. Giovanni Stanco University of Naples Federico II, Italy Email: giovanni.stanco(a)unina.it<mailto:giovanni.stanco@unina.it> Prof. Stefania Zinno University of Naples Federico II, Italy Email: stefania.zinno(a)unina.it<mailto:stefania.zinno@unina.it>

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ACM EdgeSys in Cambridge
by Aaron Ding 19 Mar '26

19 Mar '26

For RACI fellows, ----------------------------------------------- The 9th International Workshop on Edge Systems, Analytics and Networking (EdgeSys 2026), in conjunction with ACM MobiSys 2026<https://www.sigmobile.org/mobisys/2026/>, 25 June, 2026 Cambridge, United Kingdom https://edge-sys.github.io/2026/ ----------------------------------------------- The 9th International Workshop on Edge Systems, Analytics and Networking (EdgeSys 2026), in conjunction with ACM MobiSys 2026<https://www.sigmobile.org/mobisys/2026/>, aims to bring together system researchers, data scientists, engineers and practitioners to identify open directions and discuss the latest research ideas and results on edge systems, analytics and networking, especially those related to novel and emerging technologies and use cases. The EdgeSys'26 workshop focuses on systems, analytics and networking aspects, covering system architecture, distributed ML algorithms, decentralized networking, distributed consensus and ledger techniques, edge services and data analysis. Over the past eight years, EdgeSys has been gathering substantial community contributions in edge computing domain - especially with high quality TPC, keynotes, panel and technical papers from US, Europe, and Asia, including Google, Amazon, Facebook, Microsoft Research, Intel, IBM, Nokia, Samsung, Toyota, Telefónica, MIT, Berkeley, Columbia, Yale, UCLA, Cambridge, Imperial, EPFL, TU Delft, MPI, TUM, Tsinghua, Peking and Fudan. EdgeSys Programme Committee: https://edge-sys.github.io/2026/committee.html The topics include but are not limited to the following: * System Architecture for Edge Computing * Serverless, In-network Computing * Edge Storage Systems * Distributed ML for Edge Analytics and Services * Edge-driven Data Analytics * Federated Learning at the Edge * Lightweight Virtualization for Edge Computing * Distributed Consensus Algorithms and Ledgers * Infrastructure and Toolkits for Edge AI * Trustworthy Edge AI * Sustainable Edge Computing * Energy-driven Edge Computing * IoT Networking and Communications * Sensor Networks and Processing * (Autonomous) Management for Edge Systems * System Performance and Measurement * Security and Trust Management * Reliability and Fault Tolerance * Privacy-Preserving Analytics * Data Provenance for Distributed Processing * Heterogeneous & Scalable Orchestration * Edge Architectures for 5G and Beyond Submission Guidelines Authors are encouraged to submit papers describing original and unpublished research, not currently under review in other venues. In particular, innovative, early-stage ideas and preliminary results are welcome. Papers must be submitted electronically as PDF files, formatted for 8.5x11-inch paper. The length of the paper must be no more than 6 pages in the ACM double-column format (10-pt font), excluding references and appendices. Authors are suggested to use the ACM Master article template with the \documentclass[sigconf,10pt]{acmart} option. The reviews will be single blind. The first page must contain an abstract, the name(s) and affiliation(s) of the author(s), as well as the corresponding contact information. Each submission will receive independent, blind peer reviews from the program committee. Accepted papers will be published in the ACM Digital Library. At least one of the authors of every accepted paper must register and present the paper at the workshop. The program committee will elect one paper for the Best Paper Award. Important Dates * Submission deadline: 22 March 2026 (AoE, firm) * Acceptance notification: 24 April 2026 * Camera ready: 30 April 2026 * Workshop date: 25 June 2026 Programme General Chairs Atakan Aral (University of Vienna, Austria) Poonam Yadav (University of York, UK) Vadim Safronov (University of Oxford, UK) Aaron Ding (TU Delft, Netherlands) Submission Site: https://edgesys26.hotcrp.com/

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CfP - IEEE MNC Special Session on AI-Native and Data-Driven Management for Next-Generation Networks
by GIOVANNI STANCO 10 Mar '26

10 Mar '26

================================================================================ CALL FOR PAPERS Special Session: AI-Native and Data-Driven Management for Next-Generation Networks Part of the 2026 IEEE International Symposium on Measurement in Networking and Communications Napoli, Italy - July 13-16, 2026 https://mnc2026.ieee-ims.org/program/special-sessions#session-1-1 ================================================================================ We invite the submission of original research contributions to the Special Session on AI-Native and Data-Driven Management for Next-Generation Networks, organized within the framework of the 2026 IEEE International Symposium on Measurement in Networking and Communications, held in Napoli, Italy, July 13-16, 2026. AI-Native and Data-Driven Management is important and promising for Measurement in Networking since it will enable automatic optimization and network management. Over the years, Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly pervasive in networking and communications, playing a key role in the development, deployment, and management of next-generation networks. Current research trends show how AI can enhance 5G networks at at the RAN, Edge, and Core layers, using measured data coming from multiple entities. While AI adoption in 5G has been an evolving process, 6G is envisioned as truly AI-native. The next generation of mobile networks will embed "connected intelligence" throughout its architecture, leveraging AI for network design, optimization, and autonomous operation. In 6G, AI will not only enhance network performance but also enable and support AI-driven services running seamlessly across the entire network from the user equipment to the network core. Through this AI-native framework, the network will be capable of analyzing real-time data to jointly orchestrate functions such as scheduling, network slicing, and strategic planning. AI technologies in fact, expand new potential in the optimization of the full end-to-end chain of the physical layer, from the transmitter to the receiver, enabling self-optimization by combining advanced sensing and data collection also introducing the capability to consider network metrics, such as current spectrum, power conditions, and number of connections, evolving because of signal reflections off buildings and weather patterns for constant re-optimization. Monitoring of real-time environmental and contextual data is a promising enabler for ML-based air interface optimization, leading to more efficient spectrum use and reduced latency. Not only, nowadays, AI is now further enhanced and made more interpretable through XAI methodologies, which allow us to better understand how the algorithms operate and which features are most relevant for predictions. Topics of interest include, but are not limited to: * Measurements for 6G, beyond-5G, and next-generation communications * Trustworthy AI and explainable measurement approaches * AI/ML-driven network measurement and diagnostics * Software-defined and virtualized network measurement * Big Data analytics for network traffic, QoS, and QoE evaluation * Security, privacy, and reliability network measurements in 5G and 6G ***Timeline*** Paper registration: April 6, 2026 Initial manuscript deadline: April 6, 2026 ***Manuscript submission information*** Authors are invited to submit a Full Paper (4-6 pages) reporting original research of a theoretical or applied nature using the online submission system, EDAS. EDAS Submission Link: https://edas.info/N34568 Further information available: https://mnc2026.ieee-ims.org/author-information ***Special Session Chairs*** Prof. Giovanni Stanco University of Naples Federico II, Italy Email: giovanni.stanco(a)unina.it<mailto:giovanni.stanco@unina.it> Prof. Stefania Zinno University of Naples Federico II, Italy Email: stefania.zinno(a)unina.it<mailto:stefania.zinno@unina.it>

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