Edge-Based Federated Deep Reinforcement Learning for IoT Traffic Management
Author:
Affiliation:
1. Data Analytics Department, Lytica Inc., Kanata, ON, Canada
2. Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada
Funder
Cisco Chair on Sensor Technology for the Internet of Things
NSERC/Cisco Industrial Research Chair on Sensor Networks for the Internet of Things
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/6488907/10049212/09772619.pdf?arnumber=9772619
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1. Balancing backhaul load in heterogeneous cloud radio access networks
2. Efficient Federated Learning Algorithm for Resource Allocation in Wireless IoT Networks
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5. Deep Reinforcement Learning for Internet of Things: A Comprehensive Survey
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