DocumentCode
244206
Title
Principles of Software-Defined Elastic Systems for Big Data Analytics
Author
Hong Linh Truong ; Dustdar, Schahram
fYear
2014
fDate
11-14 March 2014
Firstpage
562
Lastpage
567
Abstract
Techniques for big data analytics should support principles of elasticity that are inherent in types of data and data resources being analyzed, computational models and computing units used for analyzing data, and the quality of results expected from the consumer. In this paper, we analyze and present these principles and their consequences for software-defined environments to support data analytics. We will conceptualize software-defined elastic systems for data analytics and present a case study in smart city management, urban mobility and energy systems with our elasticity supports.
Keywords
Big Data; data analysis; big data analytics techniques; computational models; computing units; data resources; data types; elasticity supports; energy systems; smart city management; software-defined elastic systems; software-defined environments; urban mobility; Analytical models; Big data; Cities and towns; Computational modeling; Data models; Elasticity; Software;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Engineering (IC2E), 2014 IEEE International Conference on
Conference_Location
Boston, MA
Type
conf
DOI
10.1109/IC2E.2014.67
Filename
6903529
Link To Document