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Manoj Poudel, Rashmi P. Sarode, Yutaka Watanobe, Maxim Mozgovoy and Subhash Bhalla
The rise of big data has resulted in the proliferation of numerous heterogeneous data stores. Even though multiple models are used for integrating these data, combining such huge amounts of data into a single model remains challenging. There is a need in...
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Antonios Makris, Ioannis Kontopoulos, Evangelos Psomakelis, Stylianos Nektarios Xyalis, Theodoros Theodoropoulos and Konstantinos Tserpes
Edge computing constitutes a promising paradigm of managing and processing the massive amounts of data generated by Internet of Things (IoT) devices. Data and computation are moved closer to the client, thus enabling latency- and bandwidth-sensitive appl...
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R. A. Bagutdinov,M. F. Stepanov
Pág. 39 - 44
The paper analyzes the existing methods for processing big data, which can be applied to the processing of heterogeneous and multi-scale data. In this work, heterogeneous data is understood as any data with high variability of data types, formats and nat...
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Qasem Kharma,Nidal M Turab,Qusai Shambour,Mohammad Hassan
Pág. pp. 44 - 60
Smart mobile devices and cloud computing are widely used today. While mobile and portable devices have different capabilities, architectures, operating systems, and communication channels than one another, government data are distributed over heterogeneo...
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Luca Bixio, Giorgio Delzanno, Stefano Rebora and Matteo Rulli
The Internet of Things (IoT) has created new and challenging opportunities for data analytics. The IoT represents an infinitive source of massive and heterogeneous data, whose real-time processing is an increasingly important issue. IoT applications usua...
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