Tail-based Sampling

Tail-Based Sampling is a distributed tracing sampling strategy that belongs to the class of trace-level sampling techniques, distinguished by its decision-making process which occurs after the entire trace has been observed, enabling selective retention of traces based on their complete runtime characteristics.

17

Publications

720

Citations

46

Authors

23

Institutions

Publications per year

2017–2026

2

Authors

46

  1. DB
    D. B. Owen

    Southern Methodist University, United States

    2 publications · 82 citations

    2

    h-index

  2. CL
    Carsten Lund

    AT&T (United States), United States

    2 publications · 200 citations

    2

    h-index

  3. ND
    Nick Duffield

    AT&T (United States), United States

    2 publications · 200 citations

    2

    h-index

  4. MT
    Mikkel Thorup

    AT&T (United States), United States

    2 publications · 200 citations

    2

    h-index

  5. CN
    Clifford Nowell

    Weber State University, United States

    2 publications · 128 citations

    2

    h-index

1–5 of 46

Venues

  1. Laboratory Animals

    2 publications · 77 citations

    2

    h-index

  2. Journal of Marketing Research

    2 publications · 128 citations

    2

    h-index

  3. Technometrics

    2 publications · 82 citations

    2

    h-index

  4. Annals of Operations Research

    1 publications · 14 citations

    1

    h-index

  5. Operations Research Letters

    1 publications · 15 citations

    1

    h-index

1–5