Search Results for author:
Found 3 papers, 0 papers with code
A Reinforcement Learning Approach to Optimize Available Network Bandwidth Utilization
We also show that, unlike a greedy algorithm, our devised RL-based algorithm can avoid network congestion and fairly share the available network resources among contending transfers.
Multibit Tries Packet Classification with Deep Reinforcement Learning
By exploiting the sparsity of ruleset, our algorithm uses a few effective bits (EBs) to extract a large number of candidate rules with just a few of memory access.
Many Field Packet Classification with Decomposition and Reinforcement Learning
Our method consists of the decomposition of fields into subsets and building separate decision trees on those subsets using a deep reinforcement learning procedure.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
