Cloud agnostic Big Data platform focusing on scalability and cost-efficiency

Lovas, Róbert and Nagy, Enikő and Kovács, József (2018) Cloud agnostic Big Data platform focusing on scalability and cost-efficiency. ADVANCES IN ENGINEERING SOFTWARE, 125. pp. 167-177. ISSN 0965-9978 10.1016/j.advengsoft.2018.05.002

[img] Text
Restricted to Registered users only

Download (1MB) | Request a copy


Nowadays a significant part of the cloud applications processes a large amount of data to provide the desired analytics, simulation and other results. Cloud computing is becoming a widely used IT model to address the needs of many scientific and commercial Big Data applications. In this paper, we present a Hadoop platform deployment method for various cloud infrastructures with the Occopus cloud orchestrator tool. Our automated solution provides an easy-to-use, portable and scalable way to deploy the popular Hadoop platform with the main goal to avoid vendor locking issues, i.e. there is no dependency on any cloud provider prepared and offered virtual machine image or "black-box" Platform as a Service mechanism. The paper presents promising performance measurements results and cost analysis.

Item Type: Article
Uncontrolled Keywords: Scalability; Cloud computing; orchestration; big data; MapReduce; Hadoop; Computer Science, Interdisciplinary Applications; Computer Science, Software Engineering; Occopus; Contextualisation;
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Laboratory of Parallel and Distributed Systems
SWORD Depositor: MTMT Injector
Depositing User: MTMT Injector
Date Deposited: 08 Jan 2019 21:13
Last Modified: 10 Jan 2019 11:06

Update Item Update Item