Serverless Performance Optimization

Serverless Performance Optimization is a performance optimization methodology that specifically addresses the unique constraints and characteristics of serverless computing environments, distinguishing itself from traditional optimization approaches by focusing on event-driven execution, cold start mitigation, resource allocation granularity, and ephemeral state management inherent to Function-as-a-Service platforms.

58

Publications

2.7K

Citations

194

Authors

87

Institutions

Publications per year

2017–2026

58

Authors

194

  1. RF
    Rodrigo Fonseca

    John Brown University, United States

    3 publications · 290 citations

    3

    h-index

  2. MS
    Mohammad Shahrad

    Princeton University, United States

    3 publications · 281 citations

    3

    h-index

  3. RC
    Ruichuan Chen

    Max Planck Institute for Software Systems, Germany

    2 publications · 79 citations

    2

    h-index

  4. JG
    Johannes Grohmann

    University of Würzburg, Germany

    2 publications · 83 citations

    2

    h-index

  5. SE
    Sameh Elnikety

    Microsoft (United States), United States

    2 publications · 57 citations

    2

    h-index

1–5 of 194

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 279 citations

    4

    h-index

  2. Journal of Parallel and Distributed Computing

    2 publications · 72 citations

    2

    h-index

  3. Multimedia Tools and Applications

    1 publications · 15 citations

    1

    h-index

  4. 1

    h-index

  5. IEEE Access

    1 publications · 37 citations

    1

    h-index

1–5