Linh Manh Pham

Main Article Content


The Internet of Things (IoT) is an evolution of connected networks including million chatty embedded devices. A huge amount of data generated day by day by things must be aggregated and analyzed with technologies of the "Big Data Analytics". It requires coordination of complex components deployed both on premises and Cloud platforms. This article proposes BDAaaS, a flexibly adaptive cloud-based framework for real-time Big Data analytics. The framework collects and analyzes data for IoT applications reusing existing components such as IoT gateways, Message brokers and Big Data Analytics platforms which are deployed automatically. We demonstrate and evaluate BDAaaS with the implementation of a smart-grid usecase using dataset originating from a practical source. The results show that our approach can generate predictive power consumption fitting well with real consumption curve, which proves its soundness.