Machine Learning-based Load Balancing
Machine Learning-Based Load Balancing is a load balancing approach that employs machine learning algorithms to dynamically predict and distribute workloads across computing resources by learning from historical and real-time system performance data.
122
Publications
3.8K
Citations
411
Authors
199
Institutions
Publications per year
2017–2026
97
Parents
122
Machine Learning-Based Load Balancing Algorithms in Future Heterogeneous Networks: A Survey
Emre Güreş, Ibraheem Shayea, Mustafa Ergen et al. · IEEE Access · 2022 · 107 citations · Full text
1–5 of 122
411
National University of Computer and Emerging Sciences, Pakistan
4 publications · 101 citations
4
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4
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3
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Western Norway University of Applied Sciences, Norway
3 publications · 95 citations
3
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3
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1–5 of 411
199

Beijing University of Posts and Telecommunications
Beijing, China
7 h-index
28 publications
1.2K citations
Universitat Politècnica de Catalunya
Barcelona, Spain
4 h-index
12 publications
639 citations
Tsinghua University
Beijing, China
4 h-index
6 publications
168 citations
Western Norway University of Applied Sciences
Bergen, Norway
4 h-index
6 publications
185 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
8 publications
184 citations

Western University
London, Canada
3 h-index
8 publications
264 citations

Qatar University
Doha, Qatar
3 h-index
3 publications
144 citations
National University of Computer and Emerging Sciences
Islamabad, Pakistan
3 h-index
4 publications
82 citations
1–8 of 199
7 publications · 383 citations
7
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3 publications · 199 citations
3
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2 publications · 43 citations
2
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2 publications · 42 citations
2
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2 publications · 124 citations
2
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