23 citations · 58 across the 52 of their papers we have counts for
13 papers · 1 filter
Scheduling in Quantum Satellite Networks: Fairness and Performance Optimization
Ashutosh Jayant Dikshit, Naga Lakshmi Anipeddi, Prajit Dhara +5
Quantum satellite networks offer a promising solution for achieving long-distance quantum communication by enabling entanglement distribution across global scales. This work formul…
TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis
Austin Feng, Andreas Varvarigos, Ioannis Panitsas +7
Modern enterprises generate vast streams of time series metrics when monitoring complex systems, known as observability data. Unlike conventional time series from domains such as c…
5GC-Bench: A Framework for Stress-Testing and Benchmarking 5G Core VNFs
Ioannis Panitsas, Tolga O. Atalay, Dragoslav Stojadinovic +2
The disaggregated, cloud-native design of the 5G Core (5GC) enables flexibility and scalability but introduces significant challenges. Control-plane procedures involve complex inte…
SlicePilot: Demystifying Network Slice Placement in Heterogeneous Cloud Infrastructures
Ioannis Panitsas, Tolga O. Atalay, Dragoslav Stojadinovic +2
Cellular networks are comprised of software-based entities, with main functions encapsulated as Virtual Network Functions (VNFs) deployed on Commercial-off-the-Shelf (COTS) hardwar…
Agoran: An Agentic Open Marketplace for 6G RAN Automation
Ilias Chatzistefanidis, Navid Nikaein, Andrea Leone +5
Next-generation mobile networks must reconcile the often-conflicting goals of multiple service owners. However, today's network slice controllers remain rigid, policy-bound, and un…
D2Q Synchronizer: Distributed SDN Synchronization for Time Sensitive Applications
Ioannis Panitsas, Akrit Mudvari, Leandros Tassiulas
In distributed Software-Defined Networking (SDN), distributed SDN controllers require synchronization to maintain a global network state. Despite the availability of synchronizatio…
FedJam: Multimodal Federated Learning Framework for Jamming Detection
Ioannis Panitsas, Iason Ofeidis, Leandros Tassiulas
Jamming attacks pose a critical threat to wireless networks, yet existing detection methods remain largely unimodal, centralized and resource-intensive, limiting their performance,…
JamShield: A Machine Learning Detection System for Over-the-Air Jamming Attacks
Ioannis Panitsas, Yagmur Yigit, Leandros Tassiulas +2
Wireless networks are vulnerable to jamming attacks due to the shared communication medium, which can severely degrade performance and disrupt services. Despite extensive research,…
TRACE: Grounding Time Series in Context for Multimodal Embedding and Retrieval
Jialin Chen, Ziyu Zhao, Gaukhar Nurbek +5
The ubiquity of dynamic data in domains such as weather, healthcare, and energy underscores a growing need for effective interpretation and retrieval of time-series data. These dat…
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
Neil He, Rishabh Anand, Hiren Madhu +5
Large language models (LLMs) have shown great success in text modeling tasks across domains. However, natural language exhibits inherent semantic hierarchies and nuanced geometric…
Ethereum Price Prediction Employing Large Language Models for Short-term and Few-shot Forecasting
Eftychia Makri, Georgios Palaiokrassas, Sarah Bouraga +2
Cryptocurrencies have transformed financial markets with their innovative blockchain technology and volatile price movements, presenting both challenges and opportunities for predi…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
Jialin Chen, Aosong Feng, Ziyu Zhao +7
Understanding the relationship between textual news and time-series evolution is a critical yet under-explored challenge in applied data science. While multimodal learning has gain…