Deakin University
Browse

Active Queue Management in L4S with Asynchronous Advantage Actor-Critic: A FreeBSD Networking Stack Perspective

Download (17.88 MB)
journal contribution
posted on 2024-08-16, 05:26 authored by Deol Satish, Jonathan KuaJonathan Kua, Shiva PokhrelShiva Pokhrel
Bufferbloat is one of the leading causes of high data transmission latency and jitter on the Internet, which severely impacts the performance of low-latency interactive applications such as online streaming, cloud-based gaming/applications, Internet of Things (IoT) applications, voice over IP (VoIP), real-time video conferencing, and so forth. There is currently a pressing need for developing Transmission Control Protocol (TCP) congestion control algorithms and bottleneck queue management schemes that can collaboratively control/reduce end-to-end latency, thus ensuring optimal quality of service (QoS) and quality of experience (QoE) for users. This paper introduces a novel solution by experimentally integrate the low latency, low loss, and scalable throughput (L4S) architecture (specified by the IETF in RFC 9330) in FreeBSD framework with the asynchronous advantage actor-critic (A3C) reinforcement learning algorithm. The first phase involves incorporating a modified dual-queue coupled active queue management (AQM) system for L4S into the FreeBSD networking stack, enhancing queue management and mitigating latency and packet loss. The second phase employs A3C to adjust and fine-tune the system performance dynamically. Finally, we evaluate the proposed solution’s effectiveness through comprehensive experiments, comparing it with traditional AQM-based systems. This paper contributes to the advancement of machine learning (ML) for transport protocol research in the field. The experimental implementation and results presented in this paper are made available through our GitHub repositories.

History

Journal

Future Internet

Volume

16

Article number

265

Pagination

1-37

Location

Basel, Switzerland

Open access

  • Yes

ISSN

1999-5903

eISSN

1999-5903

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Issue

8

Publisher

MDPI

Usage metrics

    Research Publications

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC