Dynamic Network Bandwidth Resizing for Big Data Applications

Big Data concerns processing of large volumes of digital data with high velocity and variety. Big Data technologies allow the analysis of data in real time, which is critical for various eScience applications. In order to meet the growing demand of Big Data applications, the infrastructures must be...

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Bibliographic Details
Published in2017 IEEE 13th International Conference on e-Science (e-Science) pp. 423 - 431
Main Authors Diniz Rossi, Fabio, Da Cunha Rodrigues, Guilherme, Calheiros, Rodrigo N., Da Silva Conterato, Marcelo
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Bandwidth
Big Data
Big Data applications
eScience applications
Ports (Computers)
Protocols
Routing
Software-Defined Networking
Substrates
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Summary:Big Data concerns processing of large volumes of digital data with high velocity and variety. Big Data technologies allow the analysis of data in real time, which is critical for various eScience applications. In order to meet the growing demand of Big Data applications, the infrastructures must be flexible enough to adapt to the characteristics of the applications. Most of the solutions presented in the literature to support Big Data applications focus on scaling processors and memory to handle a variable demand from applications. In a complementary way, this article targets the problem of adapting the network bandwidth to the amount of data to be transferred to and from the applications in order to improve the performance of the applications. For this purpose, we propose the use link aggregation protocol along with Software-Defined Network capabilities for management of the network flow. Results showed that the proposed approach improves the application's performance by up to 33%.
DOI:10.1109/eScience.2017.56