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A Quantitative Review on Introducing the Election Process with Cloud Based Electronic Voting and Measuring the Performance using Map Reduce
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.
Hadoop, Online Voting, Web Technologies.
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