Total views : 242

A Quantitative Review on Introducing the Election Process with Cloud Based Electronic Voting and Measuring the Performance using Map Reduce

Affiliations

  • School of Information Technology and Engineering, VIT University, Near Katpadi Road, Vellore - 632014, Tamil Nadu, India

Abstract


The measure of information created consistently in an advanced domain is expanding in an exponential rate. The increased accessibility of the system is strongly affected by the structure and high volume of data. The advancement in the web technologies gave rise to many applications and among them is online voting system which makes the voting process very easy and efficient. In developing countries, with millions of people voting through the system creates a huge amount of data which makes the data processing more complex. To make effective voting process the primary need is infrastructure and maintaining the infrastructure is one of the key task. However there exist different cloud service providers, choosing the appropriate is always challenging. The efficiency of the system is in the counting process, where a large set of data is to be processed. In this review, we discuss the election process using cloud and vote counting using Map Reduce. Hadoop gives better devices and methods to handle this colossal measure of information. The performance is measured by taking input from the voting application and then analysed. The parameters considered are the measure of bytes composed, read by the framework and the current state of the Hadoop system on increased file size. The proposed system for processing voting data shows that time and processing speed do not increase proportionally to the file count.

Keywords

Hadoop, Online Voting, Web Technologies.

Full Text:

 |  (PDF views: 200)

References


  • Anand Ankit, Divya Pallavi. An Efficient Online Voting System. International Journal of Modern Engineering Research. 2012 July-Aug; 2(4).
  • Agrawal Sanjay, Pal Amrit, Agrawal Pinki, Jain Kunal. A Performance Analysis of MapReduce Task with Large Number of Files Dataset in Big Data Using Hadoop, IEEE. 2014; DOI: 10.1109/ICICA.2014.16.
  • Gupta Ashutush, Dhyani Praveen, Rishi OP. Cloud based e-voting: one step ahead for good governance in India. International Journal of Computer Application. 2013 April; 7(02).
  • Nadaph Anisara, Katiyar Ashmita, Gosami Durgesh Kumari. An Analysis of secure online voting system. International Journal of Innovative Research in Computer Science and Technology. 2014 Sep; 2(5).
  • Zhouwei, Pierre Guillaume and Chi-Hung Chi. Cloud TPS: Scalable Transactions for web applications in the cloud. IEEE transactions of scalable computing. 2012 Dec; 5(04).
  • Megiba Jasmine R and Nishiba GM. Public Cloud secure group sharing and accessing in cloud computing. Indian Journal of Science and Technology. 2015 July; 8(15).
  • Bhosale Poonam, Vethaka Priyanaka, Thorat Lata, Archana Lomte. Identity Access Management using Multitier Cloud Infrastructure for secure online voting system. IJMRD 2015 March; 2(4).
  • Shymala K, Sunitha Rani T. An analysis on efficient resource allocation mechanism in cloud computing. Indian Journal of Science and Technology. 2015 May; 8(9).
  • Rama Satish KV, Kavya NP. Big Data Processing with harnessing Hadoop-MapReduce for Optimizing Analytical Workloads. IEEE 2014, International Conference on Contemporary Computing and Informatics.
  • Kyoo-Sungnoh and Doo-Sik-Lee. Bigdata platform design and implementation. Indian Journal of Science and Technology. 2015 Aug; 8(9).

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.