A Scalable Big Stream Cloud Architecture for the Internet of Things

Laura Belli, Simone Cirani, Luca Davoli, Gianluigi Ferrari, Lorenzo Melegari, Màrius Montón and Marco Picone
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Laura Belli: University of Parma, Parma, Italy
Simone Cirani: University of Parma, Parma, Italy
Luca Davoli: University of Parma, Parma, Italy
Gianluigi Ferrari: University of Parma, Parma, Italy
Lorenzo Melegari: University of Parma, Parma, Italy
Màrius Montón: WorldSensing, Barcelona, Spain
Marco Picone: University of Parma, Parma, Italy

International Journal of Systems and Service-Oriented Engineering (IJSSOE), 2015, vol. 5, issue 4, 26-53

Abstract: The Internet of Things (IoT) will consist of billions (50 billions by 2020) of interconnected heterogeneous devices denoted as “Smart Objects:” tiny, constrained devices which are going to be pervasively deployed in several contexts. To meet low-latency requirements, IoT applications must rely on specific architectures designed to handle the gigantic stream of data coming from Smart Objects. This paper propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from Smart Objects through a Graph-based processing platform and deliver processed data to consumer applications with low latency. The authors reverse the traditional “Big Data” paradigm, where real-time constraints are not considered, and introduce the new “Big Stream” paradigm, which better fits IoT scenarios. The paper provides a performance evaluation of a practical open-source implementation of the proposed architecture. Other practical aspects, such as security considerations, and possible business oriented exploitation plans are presented.

Date: 2015
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