Auto-scaling

Auto-Scaling is a cloud resource management framework that dynamically adjusts computing resources in response to workload fluctuations, distinguishing itself by enabling elastic scalability through automated provisioning and deprovisioning of infrastructure in accordance with predefined policies or real-time demand metrics.

462

Publications

18.2K

Citations

1.4K

Authors

513

Institutions

Publications per year

2017–2026

304

Authors

1.4K

  1. RB
    Rajkumar Buyya

    The University of Melbourne, Australia

    10 publications · 792 citations

    10

    h-index

  2. AG
    Anshul Gandhi

    Stony Brook University, United States

    8 publications · 553 citations

    8

    h-index

  3. WI
    Waheed Iqbal

    University of the Punjab, Pakistan

    7 publications · 306 citations

    7

    h-index

  4. NH
    Nikolas Herbst

    University of Würzburg, Germany

    7 publications · 264 citations

    7

    h-index

  5. SK
    Samuel Kounev

    University of Würzburg, Germany

    7 publications · 217 citations

    7

    h-index

1–5 of 1.4K

Venues

  1. Future Generation Computer Systems

    FGCS · 15 publications · 569 citations

    14

    h-index

  2. IEEE Transactions on Services Computing

    11 publications · 576 citations

    11

    h-index

  3. IEEE Access

    12 publications · 475 citations

    11

    h-index

  4. IEEE Transactions on Cloud Computing

    10 publications · 315 citations

    10

    h-index

  5. IEEE Transactions on Network and Service Management

    TNSM · 7 publications · 330 citations

    7

    h-index

1–5