Autoscaling Algorithms

Autoscaling Algorithms is a computational method within elastic resource management that dynamically adjusts the allocation of computing resources in response to varying workload demands by automatically provisioning or deprovisioning infrastructure based on predefined performance or cost-related thresholds.

101

Publications

4.1K

Citations

304

Authors

128

Institutions

Publications per year

2017–2026

65

Variants

Auto-scaling Algorithms

Authors

304

  1. AG
    Anshul Gandhi

    Stony Brook University, United States

    5 publications · 213 citations

    5

    h-index

  2. AK
    Andrzej Kochut

    IBM Research - Thomas J. Watson Research Center, United States

    5 publications · 213 citations

    5

    h-index

  3. IR
    Ilkyeun Ra

    University of Colorado Denver, United States

    4 publications · 158 citations

    4

    h-index

  4. AA
    Abeer Abdel Khaleq

    University of Colorado Denver, United States

    4 publications · 158 citations

    4

    h-index

  5. CM
    Cristian Mateos

    Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina

    4 publications · 96 citations

    4

    h-index

1–5 of 304

Venues

  1. IEEE Transactions on Services Computing

    4 publications · 174 citations

    5

    h-index

  2. Future Generation Computer Systems

    FGCS · 5 publications · 180 citations

    5

    h-index

  3. IEEE Access

    3 publications · 146 citations

    3

    h-index

  4. Cluster Computing

    2 publications · 34 citations

    2

    h-index

  5. IEEE Transactions on Cloud Computing

    2 publications · 52 citations

    2

    h-index

1–5