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H. Truong:
"Principles of Software-defined Elastic Systems for Big Data Analytics - The VIECOM Approach";
Talk: Kyoto University, Kyoto, Japan (invited); 2014-11-20.

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 talk, we analyze and present these principles and their consequences for software-defined environments to support data analytics in multi-cloud environments. We will conceptualize software-defined elastic systems for data analytics, which can be seen in smart city management, urban mobility, and energy systems. Based on that, we will present our approach to achieve elasticity principles for data analytics. First, we will present designs and features of main core services for monitoring, control, deployment of elastic software services. Second, we will discuss how we virtualize and provision human-based services for harnessing people for complex data analytics. Third, we will introduce our techniques to integrate human-based services and software-based services to carry out end-to-end cloud-based data analytics in multi-cloud environments. We will illustrate a prototype for predictive maintenance in smart cities.