Cost-aware Search

Cost-Aware Search is a federated search strategy that optimizes query processing by explicitly accounting for resource expenditures—such as communication, computation, and latency costs—when determining which data sources to access and how to aggregate results across distributed repositories.

107

Publications

3.9K

Citations

305

Authors

154

Institutions

Publications per year

2017–2026

34

Authors

305

  1. CX
    Chuan Xiao

    Nagoya University, Japan

    3 publications · 58 citations

    3

    h-index

  2. ML
    Mingyan Liu

    University of Michigan, United States

    3 publications · 212 citations

    3

    h-index

  3. OF
    Ophir Frieder

    Illinois Institute of Technology, United States

    3 publications · 37 citations

    3

    h-index

  4. LR
    Louiqa Raschid

    University of Maryland, College Park, United States

    3 publications · 102 citations

    3

    h-index

  5. JQ
    Jianbin Qin

    UNSW Sydney, Australia

    3 publications · 58 citations

    3

    h-index

1–5 of 305

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 283 citations

    6

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 58 citations

    4

    h-index

  3. The VLDB Journal

    3 publications · 73 citations

    3

    h-index

  4. 2

    h-index

  5. Theoretical Computer Science

    2 publications · 30 citations

    2

    h-index

1–5