Michel, M.
, Golden, E.
, Serres, O.
, Anbar, A.
and El-Ghazawi, T.
(2017),
Open Source Private Cloud Platforms for Big Data, BIG DATA ANALYTICS FOR SENSOR-NETWORK COLLECTED INTELLIGENCE, Elsevier Inc, Atlanta, GA, [online], https://doi.org/10.1016/B978-0-12-809393-1.00003-9
(Accessed April 19, 2024)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Open Source Private Cloud Platforms for Big Data
Published
Author(s)
, , Olivier Serres, Ahmad Anbar, Tarek El-Ghazawi
Abstract
Due to its availability, Cloud computing is the de facto platform of choice for big data, where Big Data as a Service (BDaaS) is believed to be the next best thing. In this book chapter we will first introduce cloud computing, defining the advantages it provides in a big data context. Similarly, we will then establish the benefits of using private clouds, before focusing on selected open source clouds environments, studying their architecture. We will constrain our scope to some of the most prominent ones, in particular in view of big data processing. We will then establish how some big data applications can greatly benefit of accelerators, and how those accelerators can be integrated with private clouds. Finally, we will present a case study, using an On-Premise Private Cloud, to demonstrate the implementation of one such environment.Citation
BIG DATA ANALYTICS FOR SENSOR-NETWORK COLLECTED INTELLIGENCE
Publisher Info
Elsevier Inc, Atlanta, GA
Pub Type
Book Chapters
Download Paper
Keywords
Cloud, Private Cloud, Big Data, OpenNebulla, Eucalyptus, Apache CloudStack, OpenStack, Cloud Computing
Citation
Created February 10, 2017, Updated November 10, 2018