An Email based Offline Download Manager for Large Distributed File System using Hadoop MapReduce Framework

International Journal of Computer Science and Engineering
© 2014 by SSRG - IJCSE Journal
Volume 1 Issue 10
Year of Publication : 2014
Authors : Pradeep H K, Rohitaksha K, Abhilash C B

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Citation:
MLA Style:

Pradeep H K, Rohitaksha K, Abhilash C B, "An Email based Offline Download Manager for Large Distributed File System using Hadoop MapReduce Framework" SSRG International Journal of Computer Science and Engineering 1.10 (2014): 1-5.

APA Style:

Pradeep H K, Rohitaksha K, Abhilash C B,(2014). An Email based Offline Download Manager for Large Distributed File System using Hadoop MapReduce Framework. SSRG International Journal of Computer Science and Engineering 1.10, 1-5.

Abstract:

People are using P2P (Peer to Peer) network for sharing and transferring digital content contains video, audio, and any other data files over the internet from different part of the world. The general peer to peer file sharing protocols was designed to work optimally in the case that all the peers have an end node on the internet. The end peers should capable of delivering the contents in proper way with limited time constraint. To solve this problem, a method is proposed a new approach that will be implemented using email’s as a medium for data transfer and load balancing with the help of Hadoop- MapReduce framework and moreover if we use systems like Gmail and Yahoo then most of the mails would be transferred internally and with more efficiency, thus improving the overall efficiency of the internet. MapReduce is a framework which is pioneered by Goggle for distributed programming. It includes user specified Map and Reduce functions which process inputs in the form of key/value pairs. Along with the MapReduce paradigm, Hadoop also implements HDFS which is known as Hadoop distributed file system.

References:

[1] MailZoro Email Based P2P File Sharing. Ajit D Dhiwal1, Sudip Gautam2, Akshay K Singh3, Vijay K. Chaurasiya 4 IIITAllahabad, India, 211011. 
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[7] Parallel & distributed processing (ipdps), 2010 ieee international symposium on mapreduce programming with apache hadoop bhandarkar, m. ; yahoo! Inc., hadoop solutions architect. 
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Key Words:

Peer to peer (P2P), Hadoop, MapReduce, HDFS