Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/25177
Title: Adaptive hierarchical and partitioned clustering for controlling high volume traffic data streams in peer to peer networks
Researcher: Vijayakumar, M
Guide(s): Parvathi, R M S
Keywords: Adaptive hierarchical and partition clustering
Data streams
Information and communication engineering
Internet traffic
Network
Peer to peer networks
Upload Date: 17-Sep-2014
University: Anna University
Completed Date: 01/05/2012
Abstract: Peer to Peer P2P network traffic experiences a major portion of internet traffic and becomes the elementary data source while considering high volume data streams Among the different types of internet applications in today s scenario P2P network is one of the high traffic network characterized by which allows a large number of users to establish communication with each other which in turn directly access and download files from the peers machine and share the resources which are considered to be inevitable The basic requirement in the internet traffic is the classification of network to be performed for high volume data streams in P2P network In this research work the use of clustering techniques by dividing into hierarchical and partition clustering to identify interesting traffic patterns based on the volume of data from network traffic data in an efficient manner is categorized Earlier models dealt with clustering of data stream which handles network traffic that comprises of numerical data set by way of using K means algorithm whereas this proposed model works well for both numerical and categorical data set This research work has extended from numerical data set to categorical data set using K modes partition cluster algorithm for high volume data streams
Pagination: xviii,129p.
URI: http://hdl.handle.net/10603/25177
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificates.pdf4.33 MBAdobe PDFView/Open
03_abstract.pdf14.75 kBAdobe PDFView/Open
04_acknowledgement.pdf7.7 kBAdobe PDFView/Open
05_contents.pdf37.18 kBAdobe PDFView/Open
06_chapter1.pdf562.42 kBAdobe PDFView/Open
07_chapter2.pdf55.65 kBAdobe PDFView/Open
08_chapter3.pdf81.54 kBAdobe PDFView/Open
09_chapter4.pdf134.99 kBAdobe PDFView/Open
10_chapter5.pdf228.42 kBAdobe PDFView/Open
11_chapter6.pdf170.45 kBAdobe PDFView/Open
12_chapter7.pdf12.59 kBAdobe PDFView/Open
13_references.pdf189.02 kBAdobe PDFView/Open
14_publications.pdf28.5 kBAdobe PDFView/Open
15_vitae.pdf7.45 kBAdobe PDFView/Open


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