Efficient and Reliable Hybrid Cloud Architechture for Big Data

TL;DR

This paper presents a hybrid cloud architecture combining local Eucalyptus cloud and AWS to efficiently manage Bangladesh's national ID database, improving data handling and reliability.

Contribution

It introduces a novel hybrid cloud framework with a graphical interface for Bangladesh's national ID database using Hadoop and HiveQL, addressing local data challenges.

Findings

Improved data handling efficiency in Bangladesh's national ID system.

Reduced server downtime and congestion issues.

Demonstrated feasibility of hybrid cloud for large-scale national data.

Abstract

The objective of our paper is to propose a Cloud computing framework which is feasible and necessary for handling huge data. In our prototype system we considered national ID database structure of Bangladesh which is prepared by election commission of Bangladesh. Using this database we propose an interactive graphical user interface for Bangladeshi People Search (BDPS) that use a hybrid structure of cloud computing handled by apache Hadoop where database is implemented by HiveQL. The infrastructure divides into two parts: locally hosted cloud which is based on Eucalyptus and the remote cloud which is implemented on well-known Amazon Web Service (AWS). Some common problems of Bangladesh aspect which includes data traffic congestion, server time out and server down issue is also discussed.