CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 13400 > Article
Paper
16 December 2024 Evaluating machine learning-based routing algorithms on various wireless network topologies
Dana Turlykozhayeva, Sауаt Akhtanov, Dauren Zhexebay, Nurzhan Ussipov, Aiym Baigaliyeva, Waldemar Wójcik, Narkez Boranbayeva
Author Affiliations +
Proceedings Volume 13400, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2024; 134000Z (2024) https://doi.org/10.1117/12.3058676
Event: Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2024, 2024, Lublin, Poland
Abstract
Wireless networks are crucial to modern communication infrastructure, supporting a wide range of applications from personal use to industrial operations. The rapid growth of mobile devices, IoT, and advanced technologies like 5G has heightened the demand for scalable, efficient, and reliable wireless networks. Routing in wireless networks is particularly complex due to the dynamic nature of the medium, device mobility, and diverse topologies. Traditional routing algorithms, though effective in some cases, frequently fail to handle the complexities of contemporary wireless networks. Integrating machine learning technologies with routing algorithms offers a promising solution. In particular, reinforcement learning (RL) has become prevalent in routing due to its ability to operate without the need for extensive datasets. This article evaluates two RL-based routing algorithms, by comparing their average delivery times under various loads across various topologies. This study offers a comprehensive analysis that addresses the importance of different network structures, providing insights into how each algorithm performs across diverse topologies, an aspect not covered in previous surveys.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Dana Turlykozhayeva, Sауаt Akhtanov, Dauren Zhexebay, Nurzhan Ussipov, Aiym Baigaliyeva, Waldemar Wójcik, and Narkez Boranbayeva "Evaluating machine learning-based routing algorithms on various wireless network topologies", Proc. SPIE 13400, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2024, 134000Z (16 December 2024); https://doi.org/10.1117/12.3058676
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
;
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 10 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Machine learning
Model based design
Data transmission
Internet of things
Sensor networks
Systems modeling
Wireless communications
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top