Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 145 tok/s
Gemini 2.5 Pro 40 tok/s Pro
GPT-5 Medium 22 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 107 tok/s Pro
Kimi K2 195 tok/s Pro
GPT OSS 120B 446 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Survey on Improved Scheduling in Hadoop MapReduce in Cloud Environments (1207.0780v1)

Published 3 Jul 2012 in cs.DC

Abstract: Cloud Computing is emerging as a new computational paradigm shift. Hadoop-MapReduce has become a powerful Computation Model for processing large data on distributed commodity hardware clusters such as Clouds. In all Hadoop implementations, the default FIFO scheduler is available where jobs are scheduled in FIFO order with support for other priority based schedulers also. In this paper we study various scheduler improvements possible with Hadoop and also provided some guidelines on how to improve the scheduling in Hadoop in Cloud Environments.

Citations (142)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube