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The concept of pattern based data sharing in big data environments

Research Output: Contribution to journal Article Peer-review

Open access

Abstract

The staggering growth in Internet of Things (IoT) technologies is the key driver for generation of massive raw data streams in big data environments. This huge collection of raw data streams in big data systems increases computational complexity and resource consumption in cloud-enabled data mining systems. In this paper, we are introducing the concept of pattern-based data sharing in big data environments. The proposed methodology enables local data processing near the data sources and transforms the raw data streams into actionable knowledge patterns. These knowledge patterns have dual utility of availability of local knowledge patterns for immediate actions as well as for participatory data sharing in big data environments. The proposed concept has the wide potential to be applied in numerous application areas.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 11-18

Journal (Volume, Issue Number)

International Journal of Database Theory and Application (Volume 8, Issue 4)

Publication milestones

  • Published - 30/08/2015

Publication status

Published - 30/08/2015

ISSN

2005-4270

External Publication IDs

  • ORCID: /0000-0001-7428-2272/work/63072771