On Designing a Generic Framework for Cloud-based Big Data Analytics

TL;DR

This paper introduces a five-layer cloud-based big data analytics framework integrating dew and edge computing, along with a method for customizing big data stacks based on specific data and computing models.

Contribution

It proposes a novel five-layer model for cloud-based big data analytics incorporating dew and edge computing, and a customizable approach for selecting technologies.

Findings

The framework effectively integrates dew and edge computing layers.

The approach enables tailored big data stack creation for specific applications.

The model enhances scalability and flexibility in cloud-based analytics.

Abstract

Big data analytics has gathered immense research attention lately because of its ability to harness useful information from heaps of data. Cloud computing has been adjudged as one of the best infrastructural solutions for implementation of big data analytics. This research paper proposes a five-layer model for cloud-based big data analytics that uses dew computing and edge computing concepts. Besides this, the paper also presents an approach for creation of custom big data stack by selecting technologies on the basis of identified data and computing models for the application