Throughput-aware Scheduling

Throughput-Aware Scheduling is a computational scheduling methodology that prioritizes the maximization of system throughput by dynamically allocating resources and ordering tasks based on their expected contribution to overall processing efficiency, distinguishing it from latency- or fairness-oriented scheduling strategies.

252

Publications

10.6K

Citations

683

Authors

284

Institutions

Publications per year

2017–2026

44

Authors

683

  1. SS
    Sanjay Shakkottai

    The University of Texas at Austin, United States

    7 publications · 229 citations

    7

    h-index

  2. EM
    Eytan Modiano

    Massachusetts Institute of Technology, United States

    6 publications · 197 citations

    6

    h-index

  3. LY
    Lei Ying

    Arizona State University, United States

    5 publications · 101 citations

    5

    h-index

  4. NB
    Ness B. Shroff

    The Ohio State University, United States

    5 publications · 195 citations

    5

    h-index

  5. NB
    Nicholas Bambos

    Stanford University, United States

    4 publications · 121 citations

    4

    h-index

1–5 of 683

Venues

  1. IEEE/ACM Transactions on Networking

    TON · 13 publications · 1K citations

    12

    h-index

  2. IEEE Transactions on Wireless Communications

    6 publications · 220 citations

    6

    h-index

  3. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 5 publications · 118 citations

    5

    h-index

  4. IEEE Communications Letters

    5 publications · 139 citations

    5

    h-index

  5. IEEE Transactions on Information Theory

    4 publications · 423 citations

    4

    h-index

1–5