Study and analysis of big data for characterization of user association in large scale

Wei-wei Zhang (), Jyoti Bhola (), Rajeev Kumar () and Nitin Saluja ()
Additional contact information
Wei-wei Zhang: Xian University of Posts and Telecommunication
Jyoti Bhola: National Institute of Technology
Rajeev Kumar: Chitkara University
Nitin Saluja: Chitkara University

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 1, No 38, 375-384

Abstract: Abstract The volume and the data detail are increasing like social media, multimedia and internet of things produced huge data flow in structured and unstructured format. The academia, government, and industry have the great attention for data generation. The cloud computing is conjoined with the data and it provides the user ability to utilize the commodity computing for queries process through the several datasets and timely return of resultant set. The several serious challenges are produced by the amount of collected data such as transfer speed and security issues. Big Data is in its initial stage and it required to be classifies the various attributes of big data such as management and quick progression rate. The results show that the one big executer configuration performance is better as compared to the six small executer configuration. It is also observed that the more executer configuration increase the utilization of the resources and the high probability is led by the resource contention so there is negative impact on the system performance. The fewer amounts of data are produced and it performs better for other applications. The data size is not always reduced by enabling data compression. The data size is reduced up-to 72% by compression and memory serialization.

Keywords: Big data; Cloud computing; Executer configuration; Data compression; Memory serialization; Data size; System performance; Progression rate (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-021-01434-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01434-y

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-021-01434-y

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().