Hadoop Perfomance Improvement For Big Data Processing On Trans-Regional Networks Using ViNe

Abstract

The exponential growth of data continues to increase in human life, the data is sourced from sensor data, social media data and social networking service (SNS) data which is referred to as the Big Data era. As data grows bigger and faster, the cost of storing and analyzing data becomes more and more expensive. This article proposes an approach to improve Hadoop performance in a trans-regional network environment through a virtual networking tool called ViNe. This approach enables IoT-sourced Big Data to store data in geographically distributed storage. Additionally, the approach allows IoT Big Data analyzers to deploy MapReduce applications on top of a trans-regional Hadoop Distributed File System.