Smart Packet Transmission Scheduling in Cognitive IoT Systems: DDQN Based Approach-Reference-Cited by-同舟云学术

Smart Packet Transmission Scheduling in Cognitive IoT Systems: DDQN Based Approach

Published:2022 Issue: Volume:10 Page:50023-50036
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Salh Adeeb¹,Audah Lukman¹,Alhartomi Mohammed A.²^ORCID,Kim Kwang Soon³^ORCID,Alsamhi Saeed Hamood⁴^ORCID,Almalki Faris A.⁵^ORCID,Abdullah Qazwan¹^ORCID,Saif Abdu⁶^ORCID,Algethami Haneen⁷^ORCID

Affiliation:

1. Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia

2. Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia

3. School of Electrical and Electronics Engineering, Yonsei University, Seodaemun-gu, Seoul, South Korea

4. SRI, Athlone Institute of Technology, Technical University of the Shannon: Midlands Midwest, Athlone, Westmeath, Ireland

5. Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

6. Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia

7. Department of Computer Science, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

Funder

Universiti Tun Hussein Onn Malaysia

University of Tabuk, Saudi Arabia

Deanship of Scientific Research at Taif University, Saudi Arabia, through Taif University Researchers Supporting Project

European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie

Research Grant from Science Foundation Ireland (SFI) through thr Ireland’s European Structural and Investment Funds Programs and the European Regional Development Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09762815.pdf?arnumber=9762815

Reference37 articles.

1. Distributional reinforcement learning with quantile regression;dabney;Proc 32nd AAAI Conf Artif Intell (AAAI),2018

2. Distributed distributional deterministic policy gradients;barth-maron;arXiv 1804 08617,2018

3. A distributional perspective on reinforcement learning;bellemare;Proc 34th Int Conf Mach Learn (ICML),2017

4. Reinforcement learning with replacing eligibility tracess;sutton;Mach Learn,1996

5. Diversity and delay performance of max link selection relay cooperation systems over non-identical Nakagami-m fading channels

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards sustainable industry 4.0: A survey on greening IoE in 6G networks;Ad Hoc Networks;2024-12

2. Advancing 6G-IoT networks: Willow catkin packet transmission scheduling with AI and bayesian game-theoretic approach-based resource allocation.;Internet of Things;2024-04

3. Performance Analysis of Delay and Size-Dependent Scheduling for IoT-based Healthcare Traffic Using Heterogeneous Multi-Server Priority Queueing System;2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2024-02-19

4. Bandwidth allocation of URLLC for real-time packet traffic in B5G: A Deep-RL framework;ICT Express;2023-12

5. Spectrum Efficiency Enhancement for Cell-Free Massive MIMO Through Large-Scale Fading;2023 IEEE 13th International Conference on System Engineering and Technology (ICSET);2023-10-02