Work

A Reinforcement Learning Approach to the Internet QoS Routing Problems

Year: 2005

Type: conference-paper

Abstract: We present a new algorithm based on reinforcement learning for packet scheduling in routers with QoS requirements. In our approach, reinforcement learning is used to learn a scheduling policy in response to feedback from the network about the delay experienced by each traffic priority class. We construct a new traffic regulator with the stochastic learning automaton, which does not require prior knowledge of the statistics of each traffic flow and can adapt to changing traffic requirements and loads.

Source: Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications

DOI: 10.5687/sss.2005.78

Authors: Fei Qian, Hiroyuki Une, Shigeya Ikebou, Hironori Hirata

Institutions: Kanto Gakuin University, Hiroshima Kokusai Gakuin University, Chiba University

Language: English

Topic: Network Traffic and Congestion Control

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: bronze

OpenAlex ID: W2804859635

FWCI: 0.178

Cites: 1

Cited by: 1

Related to: 10