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

Authors

411

  1. MA
    Muhammad Aleem

    National University of Computer and Emerging Sciences, Pakistan

    4 publications · 101 citations

    4

    h-index

  2. UA
    Usman Ahmed

    Western Norway University of Applied Sciences, Norway

    4 publications · 124 citations

    4

    h-index

  3. AS
    Adnan Sohail

    Iqra University, Pakistan

    3 publications · 121 citations

    3

    h-index

  4. JC
    Jerry Chun‐Wei Lin

    Western Norway University of Applied Sciences, Norway

    3 publications · 95 citations

    3

    h-index

  5. JL
    Josep Ll. Berral

    Universitat Politècnica de Catalunya, Spain

    3 publications · 183 citations

    3

    h-index

1–5 of 411

Venues

  1. IEEE Access

    7 publications · 383 citations

    7

    h-index

  2. IEEE Internet of Things Journal

    3 publications · 199 citations

    3

    h-index

  3. IEEE Wireless Communications Letters

    2 publications · 43 citations

    2

    h-index

  4. 2

    h-index

  5. IEEE Transactions on Vehicular Technology

    2 publications · 124 citations

    2

    h-index

1–5