Machine learning-based online scheduling in distributed computing

DOI10.1007/978-3-031-30445-3_21zbMath1529.68061MaRDI QIDQ6135487

Dmitry Yemelyanov, Artem Bulkhak, Victor Toporkov

Publication date: 25 August 2023

Published in: Parallel Processing and Applied Mathematics (Search for Journal in Brave)

zbMATH Keywords

dynamic programmingneural networkparallel computingknapsackmachine learningonline scheduling

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27) Performance evaluation, queueing, and scheduling in the context of computer systems (68M20) Online algorithms; streaming algorithms (68W27)

Cites Work

• Unnamed Item
• Machine learning for combinatorial optimization: a methodological tour d'horizon
• A combinatorial double auction resource allocation model in cloud computing
• Backfilling with lookahead to optimize the packing of parallel jobs

This page was built for publication: Machine learning-based online scheduling in distributed computing