Relational deep reinforcement learning for routing in wireless networks
While routing in wireless networks has been studied extensively, existing protocols are
typically designed for a specific set of network conditions and so do not easily accommodate …
typically designed for a specific set of network conditions and so do not easily accommodate …
Applying graph neural network in deep reinforcement learning to optimize wireless network routing
X Xu, Y Lu, Q Fu - … Conference on Advanced Cloud and Big …, 2022 - ieeexplore.ieee.org
At present, the traffic in wireless sensor networks (WSN) is growing at an extremely fast
speed, consuming more and more network resources. This undoubtedly affects the …
speed, consuming more and more network resources. This undoubtedly affects the …
Cost-efficient federated reinforcement learning-based network routing for wireless networks
Z Abou El Houda, D Nabousli… - 2022 IEEE Future …, 2022 - ieeexplore.ieee.org
Advances in Artificial Intelligence (AI) provide new capabilities to handle network routing
problems. However, the lack of up-to-date training data, slow convergence, and low …
problems. However, the lack of up-to-date training data, slow convergence, and low …
Learning an Adaptive Forwarding Strategy for Mobile Wireless Networks: Resource Usage vs. Latency
Designing effective routing strategies for mobile wireless networks is challenging due to the
need to seamlessly adapt routing behavior to spatially diverse and temporally changing …
need to seamlessly adapt routing behavior to spatially diverse and temporally changing …
Feature engineering for deep reinforcement learning based routing
J Suárez-Varela, A Mestres, J Yu… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
Recent advances in Deep Reinforcement Learning (DRL) techniques are providing a
dramatic improvement in decision-making and automated control problems. As a result, we …
dramatic improvement in decision-making and automated control problems. As a result, we …
Intelligence in wireless network routing through reinforcement learning
One of the critical challenges in mobile wireless network is resource optimised routing of
messages without compromising the performance criteria of the network. Routing in wireless …
messages without compromising the performance criteria of the network. Routing in wireless …
A deep reinforcement learning-based routing scheme with two modes for dynamic networks
With the development of communication and transmission technologies, more and more
applications, like Internet of vehicles and tele-medicine, become more sensitive to network …
applications, like Internet of vehicles and tele-medicine, become more sensitive to network …
Introduction to the special section on deep reinforcement learning for future wireless communication networks
We are delighted to introduce the readers to this special section of the IEEE Transactions on
Cognitive Communications and Networking (TCCN), which aims at exploring recent …
Cognitive Communications and Networking (TCCN), which aims at exploring recent …
Distributed cooperative reinforcement learning for wireless sensor network routing
A Barker, M Swany - 2022 IEEE Wireless Communications and …, 2022 - ieeexplore.ieee.org
In this work we examine a specific case of wireless sensor networks (WSN) we call peer-to-
peer WSN where source and destination are both dynamic and each is subject to constraints …
peer WSN where source and destination are both dynamic and each is subject to constraints …
Packet routing with graph attention multi-agent reinforcement learning
X Mai, Q Fu, Y Chen - 2021 IEEE Global Communications …, 2021 - ieeexplore.ieee.org
Packet routing is a fundamental problem in communication networks that decides how the
packets are directed from their source nodes to their destination nodes through some …
packets are directed from their source nodes to their destination nodes through some …