Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/72831
Title: Network traffic prediction
Authors: Chow, Ming Hui
Keywords: DRNTU::Business::International business::Retail::Computer networks
Issue Date: 2017
Abstract: In order for businesses to maintain their productivity today, it iscrucial that they constantly monitor their networks to avoid potential threats such as network failures.It has become a necessity for businesses of all sizes to employ traffic monitoring tools. Traditional network traffic monitoring tools such as Netflow are restricted to collecting traffic across the Internet from routers. As networks evolve, networks can be further divided into smaller partitions called Virtual LANs.As such, there is a need to gain visibility into network information at a lower level. The purpose of this project is to understand how traffic monitoring tools work and how they are able to provide a more reliable network by analyzing the information that they provide. Using a technology called sFlow, we can obtain more information about traffic flow. By using different data visualization methods, we can analyze and draw insights from the data presented in each method. Subsequently, I implemented a web application that allows the administrators to upload traffic data and display the data in graphs. Different data visualization methods can display different aspects of the network. Organizations should make use of various data visualization tools to present a more complete view of their network. Possible future work include creating baselines to determine normal or “healthy” levels of traffic flow.
URI: http://hdl.handle.net/10356/72831
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP_REPORT_CHOWMINGHUI.pdf
  Restricted Access
1.73 MBAdobe PDFView/Open

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.