5 citations · 14 across the 10 of their papers we have counts for
5 papers · 1 filter
SAOITHE: Sustainable Age-of-Information-Based Timely Status Updating for Hardware-constrained Edge networks
Shih-Kai Chou, Maice Costa, Mihael Mohorčič +1
In future large-scale deployments of 6G and beyond networks, collecting timely information, as measured by the Age of Information (AoI) metric, is becoming increasingly important.…
Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs
Francesc Wilhelmi, Jernej Hribar, Selim F. Yilmaz +10
As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency. To unlea…
Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network
Jernej Hribar, Ivana Dusparic
Deep Reinforcement Learning (DRL) solutions are becoming pervasive at the edge of the network as they enable autonomous decision-making in a dynamic environment. However, to be abl…
Analyse or Transmit: Utilising Correlation at the Edge with Deep Reinforcement Learning
Jernej Hribar, Ryoichi Shinkuma, George Iosifidis +1
Millions of sensors, cameras, meters, and other edge devices are deployed in networks to collect and analyse data. In many cases, such devices are powered only by Energy Harvesting…
Using Deep Q-learning To Prolong the Lifetime of Correlated Internet of Things Devices
Jernej Hribar, Andrei Marinescu, George A. Ropokis +1
Battery-powered sensors deployed in the Internet of Things (IoT) require energy-efficient solutions to prolong their lifetime. When these sensors observe a physical phenomenon dist…