Talks and Poster Presentations (with Proceedings-Entry):

H. Truong, S. Dustdar:
"Principles of Software-defined Elastic Systems for Big Data Analytics";
Talk: IEEE International Workshop on Software Defined Systems, SDS 2014 in conjunction with 2014 IEEE International Conference on Cloud Engineering, IC2E 2014, Boston, Massachusetts; 2014-03-10 - 2014-03-14; in: "Proceedings of the 2014 IEEE International Conference on Cloud Engineering, IC2E 2014", IEEE, (2014), ISBN: 978-1-4799-3766-0; 562 - 567.

English 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.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Related Projects:
Project Head Schahram Dustdar:
Automatic Elasticity Provisioning Platform for Cloud Applications

Project Head Schahram Dustdar:
Cloud computing research lab

Project Head Schahram Dustdar:
Hybrid and Diversity-Aware Collective Adaptive Systems: When People Meet Machines to Build a Smarter Society

Created from the Publication Database of the Vienna University of Technology.