Distributed Edge Analytics

Distributed Edge Analytics is a computational framework that enables localized data processing and real-time analytical inference across geographically dispersed edge nodes in a cloud edge network, distinguishing itself from centralized analytics by minimizing latency, reducing bandwidth consumption, and preserving data locality through distributed computation and coordination.

5

Publications

100

Citations

18

Authors

6

Institutions

Publications per year

2017–2026

5

Authors

18

  1. LV
    Lorenzo Valerio

    Institute of Informatics and Telematics, Italy

    1 publications · 32 citations

    1

    h-index

  2. DD
    Deepak Divan

    Georgia Institute of Technology, United States

    1 publications · 17 citations

    1

    h-index

  3. DB
    Daniel Balouek‐Thomert

    Rutgers, The State University of New Jersey, United States

    1 publications · 25 citations

    1

    h-index

  4. QZ
    Qiuxi Zhu

    University of California, Irvine, United States

    1 publications · 16 citations

    1

    h-index

  5. KA
    Kavya Ashok

    Georgia Institute of Technology, United States

    1 publications · 17 citations

    1

    h-index

1–5 of 18

Venues

  1. ACM SIGMETRICS Performance Evaluation Review

    PER · 1 publications · 25 citations

    1

    h-index

  2. Pervasive and Mobile Computing

    1 publications · 32 citations

    1

    h-index

  3. Computer Networks

    1 publications · 13 citations

1–4