Resource-aware Data Management

Resource-Aware Data Management is a data management paradigm that optimizes the collection, processing, storage, and transmission of IoT-generated data by explicitly accounting for the constraints and availability of computational, communication, and energy resources in heterogeneous and dynamic environments.

21

Publications

866

Citations

83

Authors

53

Institutions

Publications per year

2017–2026

9

Authors

83

  1. HS
    Hossam S. Hassanein

    Queen's University, Canada

    2 publications · 112 citations

    2

    h-index

  2. AS
    Arnor Solberg

    SINTEF, Norway

    1 publications · 14 citations

    1

    h-index

  3. GT
    Germán Terrazas

    University of Nottingham, United Kingdom

    1 publications · 14 citations

    1

    h-index

  4. VD
    Vipin Dubey

    Indian Agricultural Statistics Research Institute, India

    1 publications · 21 citations

    1

    h-index

  5. SO
    Sharief Oteafy

    Queen's University, Canada

    1 publications · 17 citations

    1

    h-index

1–5 of 83

Venues

  1. Journal of Network and Computer Applications

    JNCA · 1 publications · 31 citations

    1

    h-index

  2. IEEE Transactions on Biomedical Engineering

    1 publications · 162 citations

    1

    h-index

  3. New Generation Computing

    1 publications · 33 citations

    1

    h-index

  4. Computers and Electronics in Agriculture

    1 publications · 21 citations

    1

    h-index

  5. IEEE Transactions on Emerging Topics in Computing

    ITETBT · 1 publications · 95 citations

    1

    h-index

1–5