CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12709 > Article
Paper
19 October 2023 Deep Q-learning network-based optimal deployment strategy for distribution IoT
Peiyao Zhang, Di Liu, Liyuan Gao, Xuxin Yang, Hongyue Ma, Xinsu Mei
Author Affiliations +
Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127092X (2023) https://doi.org/10.1117/12.2684565
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China
Abstract
Edge computing node has large data flow and large resource occupation, which is not conducive to data transmission and processing, and is not conducive to the application of edge computing in the distribution of IoT. This paper proposes an optimization algorithm for edge computing nodes based on the deep Q-learning network theory. The node deployment problem is modeled according to the goal of minimum energy consumption and minimum traffic of the network to solve the optimal strategy. The performance of the algorithm is verified by setting different network sizes and different requests. The test shows that the method used can solve the problem of excessive resource consumption on the edge side.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Peiyao Zhang, Di Liu, Liyuan Gao, Xuxin Yang, Hongyue Ma, and Xinsu Mei "Deep Q-learning network-based optimal deployment strategy for distribution IoT", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127092X (19 October 2023); https://doi.org/10.1117/12.2684565
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
 6 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Distributed computing
Fusion energy
Education and training
Information fusion
Machine learning
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top