Open Access

ARTICLE

Clustered Single-Board Devices with Docker Container Big Stream Processing Architecture

N. Penchalaiah¹, Abeer S. Al-Humaimeedy², Mashael Maashi³, J. Chinna Babu^4,*, Osamah Ibrahim Khalaf⁵, Theyazn H. H. Aldhyani⁶

1 Department of CSE, AITS, Rajampet, 516126, Andhra Pradesh, India
2 Software Engineering Department, College of Computer and Information Sciences, King Saud University, P.O. Box 103786, Riyadh, 11616, Saudi Arabia
3 Software Engineering Department, King Saud University, Riyadh, 11543, Saudi Arabia
4 Department of Electronics and Communication Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, 516126, Andhra Pradesh, India
5 Al-Nahrain University, Al-Nahrain Nanorenewable Energy Research Center, Baghdad, 10072, Iraq
6 Applied College in Abqaiq, King Faisal University, P.O. Box 400, Al-Ahsa, 31982, Saudi Arabia

* Corresponding Author: J. Chinna Babu. Email:

Computers, Materials & Continua 2022, 73(3), 5349-5365. https://doi.org/10.32604/cmc.2022.029639

Received 08 March 2022; Accepted 31 May 2022; Issue published 28 July 2022

Abstract

The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that was used to run a test application was containerized and deployed using a Raspberry Pi cluster and Docker. To obtain system data and analyze the setup’s performance a Prometheus-based stack monitoring and alerting solution in the cloud based market is employed. This Paper assesses the system’s complexity and demonstrates how containerization can improve fault tolerance and maintenance ease, allowing the suggested solution to be used in industry. An evaluation of the overall performance is presented to highlight the capabilities and limitations of the suggested architecture, taking into consideration the suggested solution’s resource use in respect to device restrictions.

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Keywords

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