ML Anthology

An Optimal Task Assignment Policy and Performance Diagnosis Strategy for Heterogeneous Hadoop Cluster

Shekhar Gupta
AAAI 2013 pp. 1664-1665
doi:10.1609/AAAI.V27I1.8497 /aaai/2013/gupta2013aaai-optimal/

Abstract

The goal of the proposed research is to improve the performance of Hadoop-based software running on a heterogeneous cluster. My approach lies in the intersection of machine learning, scheduling and diagnosis. We mainly focus on heterogeneous Hadoop clusters and try to improve the performance by implementing a more efficient scheduler for this class of cluster.

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Text

Gupta. "An Optimal Task Assignment Policy and Performance Diagnosis Strategy for Heterogeneous Hadoop Cluster." AAAI Conference on Artificial Intelligence, 2013. doi:10.1609/AAAI.V27I1.8497

Markdown

[Gupta. "An Optimal Task Assignment Policy and Performance Diagnosis Strategy for Heterogeneous Hadoop Cluster." AAAI Conference on Artificial Intelligence, 2013.](https://mlanthology.org/aaai/2013/gupta2013aaai-optimal/) doi:10.1609/AAAI.V27I1.8497

BibTeX

@inproceedings{gupta2013aaai-optimal,
  title     = {{An Optimal Task Assignment Policy and Performance Diagnosis Strategy for Heterogeneous Hadoop Cluster}},
  author    = {Gupta, Shekhar},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2013},
  pages     = {1664-1665},
  doi       = {10.1609/AAAI.V27I1.8497},
  url       = {https://mlanthology.org/aaai/2013/gupta2013aaai-optimal/}
}