A Survey of Intelligent End-to-End Networking Solutions: Integrating Graph Neural Networks and Deep Reinforcement Learning Approaches
This paper provides a comprehensive survey of the integration of graph neural networks
(GNN) and deep reinforcement learning (DRL) in end-to-end (E2E) networking solutions …
(GNN) and deep reinforcement learning (DRL) in end-to-end (E2E) networking solutions …
[HTML][HTML] Exploring deep learning approaches for video captioning: A comprehensive review
While humans can easily describe visual data at varying levels of detail, the same task
presents a significant challenge for machines. This challenge becomes even more complex …
presents a significant challenge for machines. This challenge becomes even more complex …
Quantum computing-inspired optimal power allocation mechanism in edge computing environment
Innovations in Internet of Things (IoT) technology have significantly enhanced the service
qualities of power grid organizations by incorporating smart energy distribution techniques …
qualities of power grid organizations by incorporating smart energy distribution techniques …
Software-Defined Networking Based Resilient Proactive Routing in Smart Grids Using Graph Neural Networks and Deep Q-Networks
The enhanced functionality of the smart grid depends on the robust interconnection between
its physical and cyber-layer components. Two distinct categories of control data packets …
its physical and cyber-layer components. Two distinct categories of control data packets …
Graph reinforcement learning for power grids: A comprehensive survey
The rise of renewable energy and distributed generation requires new approaches to
overcome the limitations of traditional methods. In this context, Graph Neural Networks are …
overcome the limitations of traditional methods. In this context, Graph Neural Networks are …
A Reinforcement Learning Framework for Knowledge-Defined Networking
D Zeman, I Zelinka, M Voznak - 2023 15th International …, 2023 - ieeexplore.ieee.org
The deployment of 6G networks is expected to bring fundamental improvements to network
architectures and a focus on incorporating artificial intelligence (AI) technologies. The paper …
architectures and a focus on incorporating artificial intelligence (AI) technologies. The paper …
Science DMZ Networks: How Different Are They Really?
E Mutter, S Shannigrahi - 2024 IEEE 49th Conference on Local …, 2024 - ieeexplore.ieee.org
The Science Demilitarized Zone (Science DMZ) is a network environment optimized for
scientific applications. he Science DMZ model provides a reference set of network design …
scientific applications. he Science DMZ model provides a reference set of network design …
Enhancing Accuracy of Diabetic Retinopathy Detection Using a Hybrid Approach with the Fusion of Inceptionv3 and a Stacking Ensemble Learner
Diabetic retinopathy (DR) is a severe global problem that affects millions of people
worldwide and gets worse over time. If left untreated, DR can lead to blindness. Early and …
worldwide and gets worse over time. If left untreated, DR can lead to blindness. Early and …
Routing optimization strategy for power SDN communication network based on NSGA-II
D Hong, B Qi, X Yue - International Conference on …, 2024 - spiedigitallibrary.org
Aiming at the problems of uneven link load distribution and energy waste in power
communication networks, this paper proposes a multi-objective genetic algorithm-based …
communication networks, this paper proposes a multi-objective genetic algorithm-based …