Digital Technologies
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Digital Technologies. 2015, 1(1), 39-42
DOI: 10.12691/dt-1-1-8
Open AccessOpinion Paper

Pattern-based Data Sharing in Big Data Environments

Muhammad Habib ur Rehman1, and Aisha Batool2

1Faculty of computer science and information technology, University of Malaya, Kuala Lumpur, Malaysia

2Department of Computer Science, Iqra University, Islamabad, Pakistan

Pub. Date: August 10, 2015

Cite this paper:
Muhammad Habib ur Rehman and Aisha Batool. Pattern-based Data Sharing in Big Data Environments. Digital Technologies. 2015; 1(1):39-42. doi: 10.12691/dt-1-1-8

Abstract

The staggering growth in Internet of Things (IoTs) technologies is the key driver for generation of massive raw data streams in big data environments. In addition, the 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.

Keywords:
big data edge computing cloud computing internet of things

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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