Article, 2024

QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, ISSN 0167-739X, Volume 157, Pages 250-263, 10.1016/j.future.2024.03.035

Contributors

Hudson, Nathaniel 0000-0001-7474-2689 (Corresponding author) [1] [2] [3] Khamfroush, Hana [4] Baughman, Matt [1] Lucani, Daniel E. [5] Chard, Kyle 0000-0002-7370-4805 [1] [2] [3] Foster, Ian 0000-0003-2129-5269 [1] [2] [3]

Affiliations

  1. [1] Univ Chicago, Dept Comp Sci, Chicago, IL 60637 USA
    2. [NORA names: United States; America, North; OECD];
  2. [2] Argonne Natl Lab, Data Sci & Learning Div, Lemont, IL USA
    3. [NORA names: United States; America, North; OECD];
  3. [3] Argonne Natl Lab, Data Sci & Learning Div, Lemont, IL USA
    4. [NORA names: United States; America, North; OECD];
  4. [4] Univ Kentucky, Dept Comp Sci, Lexington, KY USA
    5. [NORA names: United States; America, North; OECD];
  5. [5] Aarhus Univ, Dept Elect & Comp Engn, Aarhus, Denmark
    6. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

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Keywords

Edge intelligence, Federated learning, Quality-of-service, Serverless edge computing, Service placement

Data Provider: Clarivate

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