Efficient Load Balancing Algorithms for Edge Computing in IoT Environments-Reference-Cited by-同舟云学术

Efficient Load Balancing Algorithms for Edge Computing in IoT Environments

Published:2024-05-09 Issue: Volume:18 Page:1646-1651
ISSN:
Container-title:2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE)
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Author:

Nainwal Ankita¹,Almusawi Muntather²,Bansal Saloni³,Michaelson Jacob⁴,Kumar Suresh⁵,Sangeeta K⁶

Affiliation:

1. Graphic Era Deemed to be University,Department of Computer Science & Engineering,Dehradun

2. College of Technical Engineering, The Islamic University,Department of Computers Techniques Engineering,Najaf,Iraq

3. GLA University,Department of Computer Engineering and Applications,Mathura

4. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Chennai,India

5. Lovely Professional University,Phagwara,India

6. Institute of Aeronautical Engineering,Department of Computer Science and Engineering,Hyderabad,Telangana

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592860/10592845/10593075.pdf?arnumber=10593075

Reference36 articles.

1. Iot Data Processing and Scheduling Based on Deep Reinforcement Learning;Jiang;International Journal of Computers, Communications and Control,2023

2. Data-intensive workflow scheduling strategy based on deep reinforcement learning in multi-clouds;Zhang;Journal of Cloud Computing,2023

3. Blockchain-based collaborative edge computing: efficiency, incentive and trust;Gao;Journal of Cloud Computing,2023

4. Deep Reinforcement Learning-based Scheduling for Optimizing System Load and Response Time in Edge and Fog Computing Environments;Wang,2023

5. Systematic Approaches to Data Placement, Replication and Migration in Heterogeneous Edge-Cloud Computing Systems: A Comprehensive Literature Review;Venkatesh;Ingenierie Des Systemes dInformation,2023