Deep reinforcement learning for communication flow control in wireless mesh networks
Wireless mesh network (WMN) is one of the most promising technologies for Internet of
Things (IoT) applications because of its self-adaptive and self-organization nature. To meet …
Things (IoT) applications because of its self-adaptive and self-organization nature. To meet …
On removing routing protocol from future wireless networks: A real-time deep learning approach for intelligent traffic control
Recently, deep learning has appeared as a breakthrough machine learning technique for
various areas in computer science as well as other disciplines. However, the application of …
various areas in computer science as well as other disciplines. However, the application of …
Understanding congestion control in multi-hop wireless mesh networks
Complex interference in static multi-hop wireless mesh networks can adversely affect
transport protocol performance. Since TCP does not explicitly account for this, starvation and …
transport protocol performance. Since TCP does not explicitly account for this, starvation and …
Intelligent software-defined mesh networks with link-failure adaptive traffic balancing
K Bao, JD Matyjas, F Hu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
In the software defined networking (SDN)-based wireless mesh network (WMN) architecture
(SD-WMN), the network is monitored and managed in a centralized manner. Although the …
(SD-WMN), the network is monitored and managed in a centralized manner. Although the …
Survey on reinforcement learning applications in communication networks
Y Qian, J Wu, R Wang, F Zhu… - … of Communications and …, 2019 - ieeexplore.ieee.org
In recent years, intelligent communication has drawn huge research efforts in both academia
and industry. With the advent of 5G technology, intelligent wireless terminals and intelligent …
and industry. With the advent of 5G technology, intelligent wireless terminals and intelligent …
Wireless mesh software defined networks (wmSDN)
In this paper we propose to integrate Software Defined Networking (SDN) principles in
Wireless Mesh Networks (WMN) formed by OpenFlow switches. The use of a centralized …
Wireless Mesh Networks (WMN) formed by OpenFlow switches. The use of a centralized …
Experience-driven networking: A deep reinforcement learning based approach
Modern communication networks have become very complicated and highly dynamic, which
makes them hard to model, predict and control. In this paper, we develop a novel experience …
makes them hard to model, predict and control. In this paper, we develop a novel experience …
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 …
Openflow for wireless mesh networks
P Dely, A Kassler, N Bayer - 2011 proceedings of 20th …, 2011 - ieeexplore.ieee.org
Several protocols for routing and forwarding in Wireless Mesh Networks (WMN) have been
proposed, such as AODV, OLSR or BATMAN However, providing support for eg flow-based …
proposed, such as AODV, OLSR or BATMAN However, providing support for eg flow-based …
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 …