Message Complexity In Distributed Computation

Message Complexity in Distributed Computation is a metric in theoretical computer science that quantifies the total number of messages required by a distributed algorithm to solve a problem, distinguishing it from other complexity measures by focusing exclusively on inter-process communication overhead rather than time or computational resources.

175

Publications

9.9K

Citations

379

Authors

189

Institutions

Publications per year

2017–2026

20

Authors

379

  1. DP
    David Peleg

    Weizmann Institute of Science, Israel

    9 publications · 558 citations

    9

    h-index

  2. SK
    Shay Kutten

    Technion – Israel Institute of Technology, Israel

    6 publications · 262 citations

    6

    h-index

  3. GP
    Gopal Pandurangan

    Nanyang Technological University, Singapore

    6 publications · 168 citations

    6

    h-index

  4. SM
    Shlomo Moran

    Technion – Israel Institute of Technology, Israel

    5 publications · 283 citations

    5

    h-index

  5. BA
    Baruch Awerbuch

    Johns Hopkins University, United States

    5 publications · 146 citations

    5

    h-index

1–5 of 379

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 9 publications · 437 citations

    9

    h-index

  2. Journal of the ACM

    JACM · 7 publications · 232 citations

    7

    h-index

  3. SIAM Journal on Computing

    5 publications · 393 citations

    5

    h-index

  4. 4

    h-index

  5. IEEE Transactions on Software Engineering

    TSE · 4 publications · 185 citations

    4

    h-index

1–5