5 papers
Feature-Based Semantics-Aware Scheduling for Energy-Harvesting Federated Learning
Eunjeong Jeong, Giovanni Perin, Howard H. Yang +1
Federated Learning (FL) on resource-constrained edge devices faces a critical challenge: The computational energy required for training Deep Neural Networks (DNNs) often dominates…
Rethinking Federated Learning Over the Air: The Blessing of Scaling Up
Jiaqi Zhu, Bikramjit Das, Yong Xie +2
Federated learning facilitates collaborative model training across multiple clients while preserving data privacy. However, its performance is often constrained by limited communic…
Battery-aware Cyclic Scheduling in Energy-harvesting Federated Learning
Eunjeong Jeong, Nikolaos Pappas
Federated Learning (FL) has emerged as a promising framework for distributed learning, but its growing complexity has led to significant energy consumption, particularly from compu…
Analysis of Age of Information for A Discrete-Time hybrid Dual-Queue System
Zhengchuan Chen, Yi Qu, Nikolaos Pappas +3
Using multiple sensors to update the status process of interest is promising in improving the information freshness. The unordered arrival of status updates at the monitor end pose…
Age of Information in Random Access Networks with Energy Harvesting
Fangming Zhao, Nikolaos Pappas, Meng Zhang +1
We study the age of information (AoI) in a random access network consisting of multiple source-destination pairs, where each source node is empowered by energy harvesting capabilit…