3 papers
cs.AI2024
Large Language Models for Explainable Decisions in Dynamic Digital Twins
Nan Zhang, Christian Vergara-Marcillo, Georgios Diamantopoulos +4
Dynamic data-driven Digital Twins (DDTs) can enable informed decision-making and provide an optimisation platform for the underlying system. By leveraging principles of Dynamic Dat…
cs.LG2024
Towards A Flexible Accuracy-Oriented Deep Learning Module Inference Latency Prediction Framework for Adaptive Optimization Algorithms
Jingran Shen, Nikos Tziritas, Georgios Theodoropoulos
With the rapid development of Deep Learning, more and more applications on the cloud and edge tend to utilize large DNN (Deep Neural Network) models for improved task execution eff…
cs.DC2024
Distributed Simulation for Digital Twins of Large-Scale Real-World DiffServ-Based Networks
Zhuoyao Huang, Nan Zhang, Jingran Shen +4
Digital Twin technology facilitates the monitoring and online analysis of large-scale communication networks. Faster predictions of network performance thus become imperative, espe…