Reinforcement learning based load balancing for fog-cloud computing systems: an optimization approach
Fog-cloud computing is a promising approach to enhance distributed systems’ efficiency and performance. Though, managing resources and balancing workloads in such environments remains challenging due to their inherent complexity and dynamic nature. The need for effective load-balancing techniques in...
Saved in:
Main Authors: | Al-Hashimi, Mustafa, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati |
---|---|
Format: | Article |
Published: |
Little Lion Scientific
2023
|
Online Access: | http://psasir.upm.edu.my/id/eprint/110240/ https://www.jatit.org/volumes/hundredone18.php |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Harnessing reinforcement learning in fog-cloud computing: challenges, insights, and future directions
by: Al-Hashimi, Mustafa, et al.
Published: (2024) -
Fog-cloud scheduling simulator for reinforcement learning algorithms
by: Al-Hashimi, Mustafa Ahmed Adnan, et al.
Published: (2023) -
Fog computing: Will it be the future of cloud computing?
by: Firdhous, Mohamed, et al.
Published: (2014) -
Fog offloading and task management in IoT-fog-cloud environment: review of algorithms, networks, and SDN application
by: Rezaee, Mohammad Reza, et al.
Published: (2024) -
Development of an attendance system based on cloud / fog computing
by: Younis, Mohamed I., et al.
Published: (2020)