Big Streaming Data Buffering Optimization

Abhilash Kancharla, Jongyeop Kim, Noh Jin Park, Nohpill Park

Research output: Contribution to book or proceedingConference articlepeer-review

1 Scopus citations

Abstract

With increasing content of data that is being created around the globe, there are at times the need for analyzing the data real time. Few of the constraints that come with real-time analysis of such huge amounts of data are time and infrastructure. In cases where time of analyzing the data is a key factor, analysis cannot be done on all of the data that is being generated real-time as the speed of stream overweighs the speed of the processing the same. When time is not that important of a factor, it calls upon a very high end infrastructure to process heavy incoming traffic of data. In such scenarios where the entire population (real-time streaming data) cannot be analyzed and cases where the prior information about the population size is not available, Sampling of the population can be used as an effective technique and the processing can be done on sampled data by maintaining possible error at the least.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Applied Computing and Information Technology, 3rd International Conference on Computational Science/Intelligence and Applied Informatics, 1st International Conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2016
EditorsWeimin Li, Simon Xu, Nam Nguyen, Takaaki Goto
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages218-223
Number of pages6
ISBN (Electronic)9781509048717
DOIs
StatePublished - May 1 2017
Event4th International Conference on Applied Computing and Information Technology, 3rd International Conference on Computational Science/Intelligence and Applied Informatics and 1st International Conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

NameProceedings - 4th International Conference on Applied Computing and Information Technology, 3rd International Conference on Computational Science/Intelligence and Applied Informatics, 1st International Conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2016

Conference

Conference4th International Conference on Applied Computing and Information Technology, 3rd International Conference on Computational Science/Intelligence and Applied Informatics and 1st International Conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2016
Country/TerritoryUnited States
CityLas Vegas
Period12/12/1612/14/16

Keywords

  • Big-Data Buffering
  • Minimum Sample Size
  • Normal distribution
  • Real-time sampling
  • Sampling

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