An Energy-Efficient Data Offloading Strategy for 5G-Enabled Vehicular Edge Computing Networks Using Double Deep Q-Network
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11277-024-10862-5.pdf
Reference44 articles.
1. Salah, I., Mabrook, M. M., Hussein, A. I., & Rahouma, K. H. (2021). Comparative study of efficiency enhancement technologies in 5G networks—A survey. Procedia Computer Science, 182, 150–158.
2. Merin Joshiba, J., Judson, D., & Bhaskar, V. (2023). A comprehensive review on NOMA assisted emerging techniques in 5G and beyond 5G wireless systems. Wireless Personal Communications, 130, 1–21.
3. Sicari, S., Rizzardi, A., & Coen-Porisini, A. (2020). 5G In the internet of things era: An overview on security and privacy challenges. Computer Networks, 179, 107345.
4. Li, S., Da Xu, L., & Zhao, S. (2018). 5G Internet of Things: A survey. Journal of Industrial Information Integration, 10, 1–9.
5. Ji, X., et al. (2018). Overview of 5G security technology. Science China Information Sciences, 61(8), 081301.
Cited by 11 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. A joint optimization of resource allocation management and multi-task offloading in high-mobility vehicular multi-access edge computing networks;Ad Hoc Networks;2025-01
2. Failure-aware resource provisioning for hybrid computation offloading in cloud-assisted edge computing using gravity reference approach;Swarm and Evolutionary Computation;2024-12
3. URLLC-aware and energy-efficient data offloading strategy in high-mobility vehicular mobile edge computing environments;Vehicular Communications;2024-12
4. A novel offloading strategy for multi-user optimization in blockchain-enabled Mobile Edge Computing networks for improved Internet of Things performance;Computers and Electrical Engineering;2024-10
5. An advanced deep reinforcement learning algorithm for three-layer D2D-edge-cloud computing architecture for efficient task offloading in the Internet of Things;Sustainable Computing: Informatics and Systems;2024-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3