DocumentCode :
240359
Title :
The evident use of evidence theory in big data analytics using cloud computing
Author :
Mcheick, Hamid ; Mohammad, Atif Farid
Author_Institution :
Comput. Sci. Dept., Univ. of Quebec at Chicoutimi, Chicoutimi, QC, Canada
fYear :
2014
fDate :
4-7 May 2014
Firstpage :
1
Lastpage :
6
Abstract :
We live in the world of evidence. This research survey comprises of several research works and has an example implying dempster-shafer theory of evidence. We have witnessed several advances in computational performance, which have brought us the design and development of high-performance computing simulation tools. It is a fact that we have to account for uncertainty, while generating such high-performance systems using such simulation tools can fail in service performance predictions. We have seen that evidence theory is utilized to measure uncertainty in terms of the uncertain measures of belief and plausibility. It is also witnessed in computing community that Cloud computing has provided a flexible and scalable infrastructures to grow beyond contemporary borders to the organizations as wells the users everyday use of services. It also has increased availability of high-performance computing applications to small/ medium-sized businesses as well as academic users to work with. This paper also sheds light on Cloud computing and Service-Oriented Architecture.
Keywords :
Big Data; cloud computing; data analysis; inference mechanisms; service-oriented architecture; uncertainty handling; Big Data analytics; Dempster-Shafer theory; cloud computing; evidence theory; service-oriented architecture; uncertainty measure; Abstracts; Computational modeling; Data models; Forgery; Personnel; Cloud Computing; Evidence Theory; High-Performance Computing; Simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on
Conference_Location :
Toronto, ON
ISSN :
0840-7789
Print_ISBN :
978-1-4799-3099-9
Type :
conf
DOI :
10.1109/CCECE.2014.6901158
Filename :
6901158
Link To Document :
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