A hybrid scheduler for many task computing in big data systems

DOI10.1515/amcs-2017-0027zbMath1368.68162OpenAlexW2735530642MaRDI QIDQ2011913

Joanna Kolodziej, Catalin Negru, Mariana Mocanu, Florin Pop, Laura Vasiliu, Valentin Gabriel Cristea

Publication date: 27 July 2017

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/amcs-2017-0027

zbMATH Keywords

simulationQoSscheduling heuristicsbig-data systemsmany-task computing

Mathematics Subject Classification ID

Performance evaluation, queueing, and scheduling in the context of computer systems (68M20)

Uses Software

• Hadoop
• OpenStack

Cites Work

• Simultaneous routing and flow rate optimization in energy-aware computer networks
• Decentralized job scheduling in the cloud based on a spatially generalized \textit{Prisoner's Dilemma} game
• Scheduling preemptable jobs on identical processors under varying availability of an additional continuous resource
• Scheduling problems with a common due window assignment: A survey

This page was built for publication: A hybrid scheduler for many task computing in big data systems