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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine and Deep Learning for Resource Allocation in Multi-Access Edge Computing: A Survey
Hamza Djigal, Jia Xu, Linfeng Liu, et al.
IEEE Communications Surveys & Tutorials (2022) Vol. 24, Iss. 4, pp. 2449-2494
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Wireless Powered Mobile Edge Computing Networks: A Survey
Xiaojie Wang, Jiameng Li, Zhaolong Ning, et al.
ACM Computing Surveys (2023) Vol. 55, Iss. 13s, pp. 1-37
Closed Access | Times Cited: 87
Machine Learning for Large-Scale Optimization in 6G Wireless Networks
Yandong Shi, Lixiang Lian, Yuanming Shi, et al.
IEEE Communications Surveys & Tutorials (2023) Vol. 25, Iss. 4, pp. 2088-2132
Open Access | Times Cited: 54
Resource Scheduling in Edge Computing: Architecture, Taxonomy, Open Issues and Future Research Directions
Mostafa Raeisi-Varzaneh, Omar Dakkak, Adib Habbal, et al.
IEEE Access (2023) Vol. 11, pp. 25329-25350
Open Access | Times Cited: 47
A Comprehensive Review of AI Techniques for Resource Management in Fog Computing: Trends, Challenges, and Future Directions
Deafallah Alsadie
IEEE Access (2024) Vol. 12, pp. 118007-118059
Open Access | Times Cited: 10
Real-time data visual monitoring of triboelectric nanogenerators enabled by Deep learning
H. H. Zhang, Tao Liu, Xuelian Zou, et al.
Nano Energy (2024) Vol. 130, pp. 110186-110186
Closed Access | Times Cited: 9
Resource allocation problem and artificial intelligence: the state-of-the-art review (2009–2023) and open research challenges
Javad Hassannataj Joloudari, Sanaz Mojrian, Hamid Saadatfar, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 26, pp. 67953-67996
Closed Access | Times Cited: 8
A Survey of Edge Computing Resource Allocation and Task Scheduling Optimization
Xiaowei Xu, Han Ding, Ling Wang, et al.
Communications in computer and information science (2024), pp. 125-135
Closed Access | Times Cited: 7
Comprehensive survey on resource allocation for edge-computing-enabled metaverse
Tanmay Baidya, Sangman Moh
Computer Science Review (2024) Vol. 54, pp. 100680-100680
Closed Access | Times Cited: 7
Leveraging Deep Learning to Strengthen the Cyber-Resilience of Renewable Energy Supply Chains: A Survey
Malka N. Halgamuge
IEEE Communications Surveys & Tutorials (2024) Vol. 26, Iss. 3, pp. 2146-2175
Closed Access | Times Cited: 6
Contemporary advances in multi-access edge computing: A survey of fundamentals, architecture, technologies, deployment cases, security, challenges, and directions
Mobasshir Mahbub, Raed M. Shubair
Journal of Network and Computer Applications (2023) Vol. 219, pp. 103726-103726
Open Access | Times Cited: 15
Deep reinforcement learning‐based resource allocation in multi‐access edge computing
Mohsen Khani, Mohammad Mohsen Sadr, Shahram Jamali
Concurrency and Computation Practice and Experience (2023) Vol. 36, Iss. 15
Closed Access | Times Cited: 12
Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework
Kaushik Sathupadi, Sandesh Achar, Shyam Bhaskaran, et al.
Sensors (2024) Vol. 24, Iss. 24, pp. 7918-7918
Open Access | Times Cited: 4
ESDN: edge computing task scheduling strategy based on dilated convolutional neural network and quasi-newton algorithm
Haoyu Liu, Le Tian, Maozu Guo
Cluster Computing (2025) Vol. 28, Iss. 3
Closed Access
A survey on resource scheduling approaches in multi-access edge computing environment: a deep reinforcement learning study
Ahmed A. Ismail, Nour Eldeen M. Khalifa, Reda A. El-Khoribi
Cluster Computing (2025) Vol. 28, Iss. 3
Open Access
Bibliography

Elsevier eBooks (2025), pp. 453-470
Closed Access
General theory and applications of resource optimization in wireless communications
Lie‐Liang Yang
Elsevier eBooks (2025), pp. 45-76
Closed Access
Federated Learning System for Dynamic Radio/MEC Resource Allocation and Slicing Control in Open Radio Access Network
Mario Martínez-Morfa, Carlos Ruiz De Mendoza, Cristina Cervelló-Pastor, et al.
Future Internet (2025) Vol. 17, Iss. 3, pp. 106-106
Open Access
SQID: A Deep Learning and Network Design Synergy for Next-Generation IoT Resource Allocation Management
Ali. M. A. Ibrahim, Zhigang Chen, Yijie Wang, et al.
Computer Communications (2025), pp. 108128-108128
Closed Access
REACT: Reinforcement learning and multi-objective optimization for task scheduling in ultra-dense edge networks
S. B., Rajeswari Sridhar
Ad Hoc Networks (2025), pp. 103834-103834
Closed Access
Computation Offloading for Tasks With Bound Constraints in Multiaccess Edge Computing
Kexin Li, Xingwei Wang, Qiang He, et al.
IEEE Internet of Things Journal (2023) Vol. 10, Iss. 17, pp. 15526-15536
Open Access | Times Cited: 9
Intelligent Resource Orchestration for 5G Edge Infrastructures
Rafael Moreno‐Vozmediano, Rubén Montero, Eduardo Huedo, et al.
Future Internet (2024) Vol. 16, Iss. 3, pp. 103-103
Open Access | Times Cited: 3
Energy-Efficient Integrated Sensing and Communication: A Multi-Access Edge Computing Design
Ning Huang, Chenglong Dou, Yuan Wu, et al.
IEEE Wireless Communications Letters (2023) Vol. 12, Iss. 12, pp. 2053-2057
Closed Access | Times Cited: 8
Artificial Intelligence-Defined Wireless Networking for Computational Offloading and Resource Allocation in Edge Computing Networks
Syed Danial Ali Shah, Mark Gregory, Fayçal Bouhafs, et al.
IEEE Open Journal of the Communications Society (2024) Vol. 5, pp. 2039-2057
Open Access | Times Cited: 2
Joint Task Offloading Scheduling and Resource Allocation in Air–Ground Cooperation UAV-Enabled Mobile Edge Computing
Zhufang Kuang, Yihui Pan, Fan Yang, et al.
IEEE Transactions on Vehicular Technology (2023) Vol. 73, Iss. 4, pp. 5796-5807
Closed Access | Times Cited: 5
DNN Inference Acceleration for Smart Devices in Industry 5.0 by Decentralized Deep Reinforcement Learning
Chongwu Dong, Muhammad Shafiq, Maryam M. Al Dabel, et al.
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 1519-1530
Closed Access | Times Cited: 5
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