Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency
Mobile wireless networks present several challenges for any learning system, due to
uncertain and variable device movement, a decentralized network architecture, and …
uncertain and variable device movement, a decentralized network architecture, and …
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 …
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 …
Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
Deep reinforcement learning for mobile 5G and beyond: Fundamentals, applications, and challenges
Future-generation wireless networks (5G and beyond) must accommodate surging growth in
mobile data traffic and support an increasingly high density of mobile users involving a …
mobile data traffic and support an increasingly high density of mobile users involving a …
Impact evaluation of control signalling onto distributed learning-based packet routing
RA Alliche, T da Silva Barros… - ITC-34-Teletraffic …, 2022 - hal.science
In recent years, several works have studied Multi-Agent Deep Reinforcement Learning for
the Distributed Packet Routing problem, with promising results in various scenarios where …
the Distributed Packet Routing problem, with promising results in various scenarios where …
Toward packet routing with fully distributed multiagent deep reinforcement learning
Packet routing is one of the fundamental problems in computer networks in which a router
determines the next-hop of each packet in the queue to get it as quickly as possible to its …
determines the next-hop of each packet in the queue to get it as quickly as possible to its …
RTHop: Real-time hop-by-hop mobile network routing by decentralized learning with semantic attention
Multi-access Edge Computing and ubiquitous smart devices help serve end-users efficiently
by providing emerging edge-deployed services. On the other hand, more heavy and time …
by providing emerging edge-deployed services. On the other hand, more heavy and time …
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 …
[HTML][HTML] Resource allocation in wireless networks with federated learning: Network adaptability and learning acceleration
HS Lee, DE Lee - ICT Express, 2022 - Elsevier
Deep reinforcement learning can effectively address resource allocation in wireless
networks. However, its learning speed may be slower in more complex networks and a new …
networks. However, its learning speed may be slower in more complex networks and a new …