6 papers
Uncertainty-Aware Haptic Signal Estimation for Reliable and Resource Efficient Tactile Internet
Georgios Kokkinis, Alexandros Iosifidis, Qi Zhang
The Tactile Internet aims to enable real-time remote haptic interaction; however, the high sampling rates required for transparency in haptic control often lead to severe congestio…
DeepCoT: Deep Continual Transformers for Real-Time Inference on Data Streams
Ginés Carreto Picón, Peng Yuan Zhou, Qi Zhang +1
Transformer-based models have dramatically increased their size and parameter count to tackle increasingly complex tasks. At the same time, there is a growing demand for high perfo…
Delay Bound Relaxation with Deep Learning-based Haptic Estimation for Tactile Internet
Georgios Kokkinis, Alexandros Iosifidis, Qi Zhang
Haptic teleoperation typically demands sub-millisecond latency and ultra-high reliability (99.999%) in Tactile Internet. At a 1 kHz haptic signal sampling rate, this translates int…
xHAP: Cross-Modal Attention for Haptic Feedback Estimation in the Tactile Internet
Georgios Kokkinis, Alexandros Iosifidis, Qi Zhang
The Tactile Internet requires ultra-low latency and high-fidelity haptic feedback to enable immersive teleoperation. A key challenge is to ensure ultra-reliable and low-latency tra…
PRISM: Distributed Inference for Foundation Models at Edge
Muhammad Azlan Qazi, Alexandros Iosifidis, Qi Zhang
Foundation models (FMs) have achieved remarkable success across a wide range of applications, from image classification to natural langurage processing, but pose significant challe…
Deep Reinforcement Learning-based Video-Haptic Radio Resource Slicing in Tactile Internet
Georgios Kokkinis, Alexandros Iosifidis, Qi Zhang
Enabling video-haptic radio resource slicing in the Tactile Internet requires a sophisticated strategy to meet the distinct requirements of video and haptic data, ensure their sync…