Emerging Approaches and Advances in Big Data
1
Department of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
2
Faculty of Engineering, Computing & Science, Swinburne University of Technology Sarawak Campus, Kuching 93350, Malaysia
3
School of Information Technology, Deakin University, Melbourne, VIC 3125, Australia
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(2), 213; https://doi.org/10.3390/sym11020213
Submission received: 31 January 2019
/
Accepted: 31 January 2019
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Published: 13 February 2019
(This article belongs to the Special Issue Emerging Approaches and Advances in Big Data)
This special issue of Symmetry entitled “Emerging Approaches and Advances in Big Data” consists of 17 papers [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17] that all present research in the emerging area of Big Data.
The growth of big data presents challenges, as well as opportunities, for industries and academia. Accumulated data can be extracted, processed, analyzed, and reported in time to deliver better data insights, complex patterns and valuable predictions to the design and analysis of various systems/platforms, including complex business models, highly scalable system and reconfigurable hardware and software systems, as well as wireless sensor and actuator networks.
The call for this Special Issue on Emerging Approaches and Advances in Big Data attracted a wide variety of high-quality submissions in the areas of architectures, design techniques, modeling and prototyping solutions for the design of complex business models, highly scalable system and reconfigurable hardware and software systems, and computing networks in the era of big data.
The special issue contains papers that use Big Data approaches in a wide range of research domains, including wearables, smart-cars, e-health, fog computing, electronics, and cloud-computing.
Our authors’ geographical distribution (published papers) is:
- Korea—26
- Iran—2
- Saudi Arabia—2
- India—1
- Malaysia—1
- China—13
- Macau—7
- Thailand—3
- South Africa—1
- Sweden—1
- USA—4
- Canada—1
We very much enjoyed reading such a wide variety of submissions in the area of big data. We would like to thank the editorial staff and reviewers for their efforts and help during the process.
Conflicts of Interest
The authors declare no conflict of interest.
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MDPI and ACS Style
Man, K.L.; Lee, K. Emerging Approaches and Advances in Big Data. Symmetry 2019, 11, 213. https://doi.org/10.3390/sym11020213
AMA Style
Man KL, Lee K. Emerging Approaches and Advances in Big Data. Symmetry. 2019; 11(2):213. https://doi.org/10.3390/sym11020213
Chicago/Turabian StyleMan, Ka Lok, and Kevin Lee. 2019. "Emerging Approaches and Advances in Big Data" Symmetry 11, no. 2: 213. https://doi.org/10.3390/sym11020213
APA StyleMan, K. L., & Lee, K. (2019). Emerging Approaches and Advances in Big Data. Symmetry, 11(2), 213. https://doi.org/10.3390/sym11020213
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