Interference and locality-aware task scheduling for MapReduce applications in virtual clusters

Author:

Bu Xiangping1,Rao Jia2,Xu Cheng-zhong1

Affiliation:

1. Wayne State University, Detroit, MI, USA

2. University of Colorado at Colorado Springs, Colorado Springs, CO, USA

Publisher

ACM

Reference34 articles.

1. Amazon ec2. http://aws.amazon.com/ec2/.

2. Amazon elastic mapreduce. http://aws.amazon.com/elasticmapreduce/.

3. Apache hadoop. http://hadoop.apache.org.

4. The apache mahout project. http://mahout.apache.org/.

5. Microsoft dryad project. http://research.microsoft.com/en-us/projects/dryad/.

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1. Suppressing the Interference Within a Datacenter: Theorems, Metric and Strategy;IEEE Transactions on Parallel and Distributed Systems;2024-05

2. Performance Challenges and Solutions in Big Data Platform Hadoop;Recent Advances in Computer Science and Communications;2023-11

3. Ah-Q: Quantifying and Handling the Interference within a Datacenter from a System Perspective;2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA);2023-02

4. Tereis: A Package-Based Scheduling in Deep Learning Systems;2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS);2023-01

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