Learning-Based Resource Management for Low-Power and Lossy IoT Networks-Reference-Cited by-同舟云学术

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Learning-Based Resource Management for Low-Power and Lossy IoT Networks

Published:2022-09-01 Issue:17 Volume:9 Page:16006-16016
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Musaddiq Arslan¹,Ali Rashid²^ORCID,Kim Sung Won³^ORCID,Kim Dong-Seong¹^ORCID

Affiliation:

1. ICT Convergence Research Center, Kumoh National Institute of Technology, Gumi, South Korea

2. School of Intelligent Mechatronics Engineering, Sejong University, Seoul, South Korea

3. Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, South Korea

Funder

Priority Research Centers Program

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/ielx7/6488907/9866069/09717281.pdf?arnumber=9717281

Reference40 articles.

1. Energy-efficient communication protocol for wireless microsensor networks

2. K-Means Clustering in Wireless Sensor Networks

3. Machine learning: supervised methods

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1. Adaptive Parent Change and Cell Usage Aware Objective Function for RPL in 6TiSCH Network;2024 International Conference on Information Networking (ICOIN);2024-01-17

2. A Cooperative Computation Offloading Strategy With On-Demand Deployment of Multi-UAVs in UAV-Aided Mobile Edge Computing;IEEE Transactions on Network and Service Management;2024

3. Intelligent Parent Change to Improve 6TiSCH Network Transmission Using Multi-Agent Q-Learning;IEEE Access;2024

4. Adaptive switching and routing protocol design and optimization in internet of things based on probabilistic models;International Journal of Intelligent Networks;2024

5. On the Performance of Epidemic DTN Routing on Low-Power and Lossy Networks;2023 2nd International Conference on Electronics, Energy and Measurement (IC2EM);2023-11-28

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