6 papers
Trust-Aware Topology Learning for Dynamic Decentralized Federated Learning under Adversaries
Shubham Vaishnav, Murtaza Rangwala, Ali Beikmohammadi +3
In dynamic mobile decentralized federated learning (DFL), adversaries can poison both model updates and the topology information devices use to choose collaborators. We present DMT…
Spatio-Temporal Scheduling Prediction Under Backhaul Delay for Resilient Coordinated Beamforming
Prashant Kumar Singh, Shubham Vaishnav, Ahmet Hasim Gökceoglu +1
Coordinated beamforming in distributed 5G networks relies on the timely exchange of inter-cell scheduling information, but backhaul latency makes this information stale. Even a sin…
ADORN: Adaptive Drift handling for Open RAN using Reinforcement Learning
Ashit Kumar Subudhi, Bhargav Chirumamilla, Shubham Vaishnav +5
Dynamic traffic variations in Open Radio Access Networks (O-RAN) lead to drift, which degrades the performance of Artificial Intelligence/Machine Learning (AI/ML) models. Tradition…
Dynamic and Distributed Routing in IoT Networks based on Multi-Objective Q-Learning
Shubham Vaishnav, Praveen Kumar Donta, Sindri Magnússon
IoT networks often face conflicting routing goals such as maximizing packet delivery, minimizing delay, and conserving limited battery energy. These priorities can also change dyna…
Socio-technical aspects of Agentic AI
Praveen Kumar Donta, Alaa Saleh, Ying Li +15
Agentic Artificial Intelligence (AI) represents a fundamental shift in the design of intelligent systems, characterized by interconnected components that collectively enable autono…
Adaptive Budgeted Multi-Armed Bandits for IoT with Dynamic Resource Constraints
Shubham Vaishnav, Praveen Kumar Donta, Sindri Magnússon
Internet of Things (IoT) systems increasingly operate in environments where devices must respond in real time while managing fluctuating resource constraints, including energy and…