The reinforcement learning algorithm gets the information of every path and adaptively choose the most suitable path by the artificial intelligence. The simulation results show that the proposed data scheduling algorithm with RL can significantly achieve a higher throughput than the default algorithm.
So far MPTCP use the RRDS algorithm as the default algorithm for data scheduling which transmit all the data to every path by polling without any consideration.
This work proposes a new data scheduling algorithm based on reinforcement learning(RL) with the newly introduced Deep Q Network (DQN) framework to enhance ...
Packet scheduling in MPTCP determines which path, among available paths with open windows, to send a packet so that the need for packet resequencing at the ...
SmartCC: A Reinforcement Learning Approach for Multipath TCP ...
dl.acm.org › doi › jsac.2019.2933761
In this paper, we propose a learning-based multipath congestion control approach called <italic>SmartCC</italic> to deal with the diversities of multiple ...
Earliest Completion First (ECF) is a scheduling algorithm that estimates the packet arrival time for each path before scheduling the packets so that packets can ...
The reinforcement learning algorithm gets the information of every path and adaptively choose the most suitable path by the artificial intelligence. The ...
This paper proposes a learning-based multipath congestion control approach called SmartCC, which adopts an asynchronous reinforcement learning framework to ...
Apr 1, 2023 · In this article, we propose a reinforcement learning-based multipath scheduler called MPTCP-RL to determine the optimal path set for different flows.
Due to the asynchronous design of SmartCC, the processes of model training and execution are decoupled, and the learning process will not introduce extra delay ...