A Virtual Network Performance Optimization Strategy for Cloud-based Big Data Processing

DOI

10.2991/ameii-15.2015.284How to use a DOI?

Keywords

Cloud computing; OpenStack Neutron; virtual networks; MapReduce

Abstract

With the widely use of cloud-based MapReduce frameworks, an increasing number of solutions have been proposed to optimize the performance of the cluster. Majority of the existing studies concentrate on optimizing the task scheduling or resource provisioning mechanisms to improve the platform’s data processing or communication performance separately, without an overall consideration. This paper designs and implements a novel virtual network performance optimization strategy for cloud-based big data processing, which changes the topology of virtual networks to optimize MapReduce performance. We implement our strategy (named Topology Optimized Mechanism on OpenStack Neutron) using python and integrate TOMON into Neutron as a separate plug-in to realize automatic deployment of virtual networks.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lulu Pan
PY  - 2015/04
DA  - 2015/04
TI  - A Virtual Network Performance Optimization Strategy for Cloud-based Big Data Processing
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 1538
EP  - 1541
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.284
DO  - 10.2991/ameii-15.2015.284
ID  - Pan2015/04
ER  -