A Comparative Study of Open-Source Software for Deployment and Management of Cloud Computing Utilizing a Big Data Processing Quality Model

Subject Areas : Multimedia Processing, Communications Systems, Intelligent Systems

Mahdi Jafari ¹ , Amir Kalbasi ²

1 - Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran
2 - Assistant Professor, Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran

Received: 2021-06-10 Accepted : 2022-08-22 Published : 2021-12-22

Keywords: Big Data Processing, Cloud Management, Big Data Storage, cloud computing, Quality Model,

Abstract :

Introduction: The volume of data produced by human society is growing rapidly. Data is being produced in many different industries such as manufacturing, transportation, healthcare, and social networks. Due to the volume of data being produced, data storage and processing are among the most important issues when dealing with big data. The main challenges when dealing with big data are data storage and management, data processing and analytics, and resource management to provide the infrastructure needed to support the first two mentioned challenges.  Cloud computing, due to its features and architecture, is a promising infrastructure to store and process big data. Different cloud computing deployment models exist, namely, public cloud, private cloud, community cloud, and hybrid cloud. To store and process big data in a cloud environment, individuals and organizations may be more inclined to deploy and manage private clouds to gain greater control and access to resources and their data. Numerous open-source software has been developed for the deployment and management of private clouds. Evaluating and choosing among them is a challenging task, especially for those who are new to these large-scale software systems. Furthermore, due to the continuous delivery of new releases with major changes or new features and modules for each of the cloud infrastructure management software, choosing among them could be a challenge even for an experienced user.Method: In this paper, first of all, we provide the Quality Model for Cloud Infrastructure (QMCI) for evaluation of cloud infrastructure management software. QMCI focuses on quality factors that are important when processing big data. The top-level factors of this model are 1- Functionality 2- Usability 3- Reliability 4- Supportability 5- Performance. The top-level factors are then divided into sub-factors to further refine the quality model. Metrics can be considered for the sub-factors to evaluate a cloud infrastructure management software.Discussion: Based on QMCI, multiple-criteria decision-making can be utilized to choose between cloud infrastructure management software that best suits a given set of criteria. In the remaining of this paper, three of the most popular open-source cloud infrastructure management software, namely, Eucalyptus, OpenStack, and Apache Cloud Stack are evaluated based on QMCI to compare their capabilities, weaknesses, and strengths from big data processing perspective. Previous literatures that considered the selected three cloud infrastructure management software were studies and utilized to perform the comparative study.

References:

 

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