Concepedia

Adaptive Trace Sampling

Adaptive Trace Sampling is a trace sampling method that dynamically adjusts sampling rates based on runtime system behavior, observational data, or predefined objectives to optimize trace representativeness and resource efficiency in distributed tracing systems.

2

Publications

118

Citations

7

Authors

4

Institutions

Publications per year

2017–2026

1

Parents

Publications

2

1–2 of 2

Authors

7

  1. MS
    Ming‐Hung Shu

    Cheng Shiu University, Taiwan

    1 publications · 14 citations

    1

    h-index

  2. NP
    Nohhyun Park

    University of Minnesota, United States

    1 publications · 104 citations

    1

    h-index

  3. IA
    Irfan Ahmad

    King Fahd University of Petroleum and Minerals, Saudi Arabia

    1 publications · 104 citations

    1

    h-index

  4. TW
    To‐Cheng Wang

    R.O.C Military Academy, Taiwan

    1 publications · 14 citations

    1

    h-index

  5. CA
    Carl A. Waldspurger

    Kitware (United States), United States

    1 publications · 104 citations

    1

    h-index

1–5 of 7

Institutions

4

  1. R.O.C Military Academy

    Kaohsiung City, Taiwan

    1 h-index

    1 publications

    14 citations

  2. National Kaohsiung University of Science and Technology

    Kaohsiung City, Taiwan

    1 h-index

    2 publications

    28 citations

  3. National Tsing Hua University

    Hsinchu, Taiwan

    1 h-index

    1 publications

    14 citations

  4. Cloud Computing Center

    Dongguan, China

    1 h-index

    4 publications

    416 citations

1–4 of 4

Venues

  1. Annals of Operations Research

    1 publications · 14 citations

    1

    h-index

1–1