-------- Ursprüngliche Nachricht -------- Von: Hesham ElBakoury helbakoury@GMAIL.COM Gesendet: 24. Januar 2025 23:23:57 MEZ An: itc@COMSOC.ORG Betreff: [InternetTC] Call for Papers: Fourth International Workshop on Green and Sustainable Networking (GreenNet 2025) *** Paper Submission Deadline is Extended to January 31st ****
*Call for Papers*
*Fourth International Workshop on Green and Sustainable Networking (GreenNet 2025) **In conjunction with IEEE International Conference on Communication (ICC) 2025, 8–12 June 2025 // Montreal, Canada*
*Note: Paper Submission Deadline is Extended to January 31st*
Energy efficiency and sustainability have become of paramount importance in all human activities, including the information and communication technology sector. The trade-off between availability, resiliency, programmability, and energy efficiency of networks and services is a key challenge for the next decade and monitoring methods and metrics for power consumption, energy efficiency, as well as sustainability are important, as well as benchmarking of solutions based on well-defined KPIs. For that reason, the goal of the GreenNet Workshop is to address emerging concepts and challenges related to energy efficiency and sustainability for networked services. An improved sustainability in all parts of the network in a time of increasing AI/ML usage, evolution of different novel network access technologies, the spreading of edge computing and micro-data centers and the demand in computational and data transport capacity across the edge-cloud continuum is essential.
See also: ICC 2025 Call for Workshop Paper https://icc2025.ieee-icc.org/call-workshop-papers, which includes author and submission guidelines.
*Important Dates*
- Workshop Paper Submission *Deadline: 31st January 2025* - Workshop Paper Acceptance Notification: 28 February 2025 - Camera Ready: 15 March 2025 - Registration Due for Accepted Papers: tbd - GreenNet 2025 Workshop: 8 and/or 12 June 2025 - ICC 2025 conference: 8–12 June 2025 // Montreal, Canada
*Topics of Interest*
- Traffic modeling and prediction for performance and power representation - Analytical models of network, base station, and cloud power consumption - Accuracy and granularity of traffic prediction models - Network and device management and control mechanisms - Optimization of trade-offs between energy consumption, efficiency, availability, resilience, sustainability, and performance - APIs for power management interfaces - Timing, scheduling, and orchestration of sleep modes in various network parts - Decentralized energy management, e.g., using distributed ledger technologies - Usage of digital twins to improve future networks energy consumption and efficiency - Network measurements and simulations for sustainable and energy efficient future networks - Benchmarking of energy efficiency and sustainability solutions - Holistic views on networks, applications, or services from network access to data center - Emerging networking concepts and technologies to improve energy consumption/efficiency - Sensor and industrial automation networks - Energy efficiency in 5G and 6G and Quality of Information improvement - Low Power Wide Area Networks - Improvement for wireless and wired network access including cable access networks - Intelligent data pre-selection, data storage, or data aggregation approaches to avoid traffic overhead or unnecessary transmissions - Multi-technology network access and multi-path support over multiple wireless technologies for access traffic steering, switching, splitting (ATSS) - Mutual roles in energy saving of satellite, terrestrial and non-terrestrial networks - Distributed data processing with cloud, edge cloud, fog, or serverless computing - Energy-saving Internet protocols - Energy efficient Radio Access Networks (RANs) and O-RAN - Impact of Non-Terrestrial-Network regenerative mode on O-RAN energy efficiency - Delay tolerant networking - Power and relay reduction techniques for signal propagation in fiber - Application of quantum communication and computing to improve energy efficiency - Efficiency in data center and CDN operations - Intelligent spectrum usage and spectrum sharing - Energy efficient wireless optical communication - AI/ML techniques in the context of energy consumption and efficiency - For power and performance management in virtualized environments - For energy efficiency in slicing, fog/cloud MEC virtualization, self-x technologies, adaptation, automation, and zero-touch - To improve general energy efficiency and sustainability of networks and the AI/ML techniques themselves - Usage of AI/ML for sustainable and energy efficient network management - Techniques to reduce the energy consumed by the power hungry AI/ML and LLM training - Architectural solutions toward network sustainability - Use of renewable energy or energy harvesting by network infrastructure and devices with high energy consumption - Heterogeneous cell coverage (macro, micro, pico, femto) for energy efficiency improvements - Power-aware network slicing - Role of the edge to support energy sustainable infrastructure - Optimized placement of computational, communication, and cooling facilities - Role of software in reducing network energy consumption and carbon footprint - Using SDN/NFV concepts to improve network sustainability - Comparison of virtualized and bare metal solutions - Coping with the end of Moore’s law - Role of standardization including network energy efficiency and sustainability metrics - Consideration of carbon emissions or lifecycle of devices
Authors are invited to submit original contributions (written in English) in PDF format. Only original papers not published or submitted for publication elsewhere will be considered for the workshop. See also: ICC 2025 Call for Workshop Paper https://icc2025.ieee-icc.org/call-workshop-papers, which includes author and submission guidelines. Only PDF files will be accepted for the review process and all manuscripts must be electronically submitted through EDAS. The EDAS link for paper submission: https://edas.info/N33189
*Organizing Committee:* Franco Davoli, University of Genoa and CNIT S2N National Lab, Italy (franco.davoli@unige.it) Hesham ElBakoury, Independent Consultant, Santa Clara, CA, USA (helbakoury@gmail.com) Timothy O'Farrell, University of Sheffield, UK (t.ofarrell@sheffield.ac.uk) Tobias Ho§feld, University of WŸrzburg, Germany (tobias.hossfeld@uni-wuerzburg.de) Frank Loh, University of WŸrzburg, Germany (frank.loh@uni-wuerzburg.de) Chiara Lombardo, University of Genoa and CNIT S2N National Lab, Italy (chiara.lombardo@unige.it
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