Real-Time Data Streaming Algorithms and Processing Technologies: A Survey

Alramzana Nujum Navaz, Saad Harous, Mohamed Adel Serhani, Ikbal Taleb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

With the ever-increasing generation of data, there exists a plethora of real-time streaming algorithms proposed in the literature. Enterprises are moving from massive data to quick data; therefore, they will need to use and maybe extend the latest innovative technologies for real-time stream processing. To serve this purpose the paper surveys and classifies the existing streaming data algorithms and techniques. It presents a categorization of existing recent data streaming algorithms that solve the well-known concept drift research problem. In addition, it lists the various datasets used for the purpose of validation. Finally, it highlights the remaining open research inquiries in this field.

Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages246-250
Number of pages5
ISBN (Electronic)9781728137780
DOIs
Publication statusPublished - Dec 2019
Event2019 International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2019 - Dubai, United Arab Emirates
Duration: Dec 11 2019Dec 12 2019

Publication series

NameProceedings of 2019 International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2019

Conference

Conference2019 International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2019
Country/TerritoryUnited Arab Emirates
CityDubai
Period12/11/1912/12/19

Keywords

  • Concept Drift
  • Data Streaming
  • Real-Time Data
  • Stream Processing Technologies
  • Streaming Algorithms

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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