Dissemin is shutting down on January 1st, 2025

Published in

American Scientific Publishers, Journal of Computational and Theoretical Nanoscience, 1(17), p. 92-100, 2020

DOI: 10.1166/jctn.2020.8634

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Big Mac: A Distributed PaaS Framework for on Demand Big Data Processing Using Machine Learning Techniques

Distributing this paper is prohibited by the publisher
Distributing this paper is prohibited by the publisher

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Abstract

In the age of start-ups and technical research, the demand for high-end computing power and loads of space is ever increasing. Machine learning techniques have become an inseparable part of the big data analytics. Setting up one’s own infrastructure to deal with all this vastness is usually not feasible due to high expenses and lack of desired expertise. As a solution to this problem, this paper proposes a system for Big-Data Analytics and Machine Learning based on Hadoop and Spark frameworks that also supports Operating System (OS) Rental Services. Machine Learning (ML) services provide option to use both existing inbuilt popular models or create one’s own model. OS Rental services provide users with high end infrastructure on their low-end devices on rent. The entire implementation has been made open source for ease of access and facilitating extensibility.