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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/217701
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- Title
- ANGEL flow meter software architecture design document
- Author(s)
- But, Jason
- Abstract
- The Automated Network Games Enhancement Layer (ANGEL) project aims to leverage Machine Learning (ML) techniques to automate the classification and isolation of interactive (e.g. games, voice over IP) and non-interactive (e.g. web) traffic. This information is then used to dynamically reconfigure the network to improve the Quality of Service provided to the current interactive traffic flows and subsequently deliver improved performance to the end users. Within this scope, the project will develop protocols that allow the adjustment of Consumer Premise Equipment (CPE - eg. cable/ADSL) configuration to provide better quality of service to interactive flows detected in real-time. This document describes the basic design motivation of the Flow Meter Software Component of ANGEL. The Flow Meter is responsible for capturing packets off a network connection, collating the statistical properties and forwarding this information to the Flow Classifier Component.
- Publication type
- Technical report
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies. Centre for Advanced Internet Architectures
- Source
- Centre for Advanced Internet Architectures: technical reports, No. 070228C
- Publication year
- 2007
- Keyword(s)
- ANGEL; Automated Network Games Enhancement Layer; Consumer premises equipment; Flow classifier; Flow meter; Machine learning; QoS; Quality of service
- Publisher
- Centre for Internet Architectures, Swinburne University of Technology
- Publisher URL
- http://caia.swin.edu.au/reports/
- Copyright
- Copyright © 2007 The author.
- Full text
