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An Exploration of Cloud Gaming Research in the Era of Edge Computing and AI

In today’s increasingly distributed computational landscape, cloud gaming has emerged as a transformative entertainment model. Cloud gaming refers to any...

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A Digital Twin Approach to Quantum Key Distribution Under Eavesdropping

Quantum Key Distribution (QKD) enables secure key exchange by leveraging quantum mechanics to provide theoretically unbreakable security. However, practical deploy...

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A Glimpse into Convex Agreement

Achieving agreement among the parties in a distributed system is crucial for maintaining consistent views. This becomes particularly challenging due...

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Jornadas Cluster 4 HE – Impulsando la innovación digital y la colaboración público-privada

IMDEA Networks, en colaboración con el CDTI, organiza una jornada informativa dedicada a las próximas convocatorias del WP 2025 Clúster...

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DUNE: Distributed Inference in the User Plane

Deploying Machine Learning (ML) models in the user plane enables line-rate in-network inference, reducing latency and enhancing scalability for tasks...

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Defensa Tesis Doctoral: Data-Driven Exploration of Sociological Patterns in Mobile Network Traffic Demands

This thesis explores the use of mobile network metadata to analyze human sociological behavior and activity patterns. Specifically, it investigates...

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A Scalable DNN Training Framework for Traffic Forecasting in Mobile Networks

In this seminar, Serly will present her recent work, accepted in ICMLCN 2025. The exponential growth of mobile data traffic...

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An Evaluation of RAN Sustainability Strategies in Production Networks

In this seminar, Orlando will present his work completed during his research stay at Telefónica, which was accepted at INFOCOM...

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From Idea to Reality: The Five Pillars of Sustainable Startup Growth

Each year, 50 million new startups emerge worldwide, yet only 10% can sustain themselves in the long run. Cloud computing...

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SYMBXRL: Symbolic Explainable Deep Reinforcement Learning for Mobile Networks

Deep Reinforcement Learning (DRL) is a method where an agent, through trial and error, interacts with an environment to gain...

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