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Anton Kos 1 and Saso Tomazic 1 and Jakob Salom 2 and Nemanja Trifunovic 3 and Mateo Valero 4 and Veljko Milutinovic 5
Academic Editor:Yunchuan Sun
1, Faculty of Electrical Engineering, University of Ljubljana, Trzaska Cesta 25, 1000 Ljubljana, Slovenia
2, Mathematical Institute of the Serbian Academy of Sciences and Arts, Knez Mihailova 36, 11001 Belgrade, Serbia
3, Maxeler Technologies Ltd., 1 Down Place, London W6 9JH, UK
4, Barcelona Supercomputing Center, Carrer de Jordi Girona 29, 08034 Barcelona, Spain
5, School of Electrical Engineering, University of Belgrade, Bulevar Kralja Aleksandra 73, 11000 Belgrade, Serbia
Received 18 December 2014; Accepted 9 March 2015; 30 August 2015
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Big data processing and big data applications are shifting the computing paradigms, computing concepts, and treatment of data. Big data processing is becoming increasingly important in cyber-physical systems (CPSs). CPS is a complex system integrating computation, communication, and physical processes. It can be seen as a sort of upgrade to its building blocks and elements, which enables coupling of cyber and physical worlds. Some of the technologies closely connected to the CPS are wireless sensor networks, Internet of things, and cloud computing. Wireless sensor networks, with their sensing capabilities, are considered to be a vital component of the emerging CPS [1]. Similarly, cloud computing provides computation capabilities, and Internet of Things (IoT) provides communication capabilities, and so forth. One common term that connects the abovementioned technologies and systems, including the CPS, is big data .
Managing big data is a many-sided problem. In addition to its volume, big data exhibits other unique characteristics that differentiate it from traditional data. For instance, big data analysis requires distinct processing; therefore, the design of scalable big-data systems may face a series of technical challenges [2]. Big data comes in various forms; from unstructured data to highly structured data streams. It is difficult to manage these volumes and forms of data and it is even more difficult to make sense of it by extracting some useful knowledge [3]. The majority of efficient big data systems and applications require a problem-specific solution...