Integration of Big Data and Cloud Computing: Tools, Issues, and Reliability

Integration of Big Data and Cloud Computing: Tools, Issues, and Reliability
  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-11
Year of Publication : 2022
Authors : Ranjit Rajak, Satish Chaurasiya, Anjali Choudhary
DOI : 10.14445/22315381/IJETT-V70I11P218

How to Cite?

Ranjit Rajak, Satish Chaurasiya, Anjali Choudhary, "Integration of Big Data and Cloud Computing: Tools, Issues, and Reliability," International Journal of Engineering Trends and Technology, vol. 70, no. 11, pp. 170-177, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I11P218

Abstract
Using information technology in various communication methods produces a massive amount of data. In current years, data size is increasing because of gathering business information, the Internet of Things (IoT), the enormous growth of social networks, etc. If the data size is large, it has two main issues: processing and storage. These issues can be solved using Cloud Computing. Cloud Computing provides the facility of the virtual environment. Where data is stored and processed on virtual servers. Cloud computing also provides a reliable, scalable, fault-tolerant environment to handle Big Data in Distributed Management systems. Big Data, a collection of homogeneous and heterogeneous information scaling up at very high-speed need, needs to be analysed without chance of any error and mistake, which may lead to improper and compromised evaluation from where the reliability measure needs to be adapted into the frame. This paper aims to provide detailed information regarding Big Data in Cloud Computing, such as definitions, Characteristics, technologies used, and reliability of Big Data in Cloud Computing. This paper describes the research challenges and different security aspects of Big Data. Finally, the reliability of Big data in the Cloud Computing paradigm is analysed in terms of the probability distribution.

Keywords
Big Data, Big Data Reliabilities, Hadoop, Map Reduce, Big Data Challenges, Big Data Tools and Technologies.

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