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Scalable classification of QoS for real-time interactive applications from IP traffic measurements

Scalable classification of QoS for real-time interactive applications from IP traffic measurements
Scalable classification of QoS for real-time interactive applications from IP traffic measurements
Measurement of network Quality of Service (QoS) has attracted considerable research effort over the last two decades. The recent trend towards Internet Service Providers (ISP's) offering application-specific QoS is creating possibilities for more sophisticated QoS metrics to be offered by ISP's in service level agreements. This in turn could be used for the purposes of improved network optimization and billing according to application specific QoS guarantees. We report a scalable near real-time approach using passively logging IP traffic data for classification of application latency and packet loss across a range of real-time interactive applications. We run six experiments involving Minecraft, Quake 3 Urban Terror, VLC video streaming and the commercial Wirofon VOIP application. We use a mixture of laboratory and real-world deployments, with run times ranging from hours to days, and observe a combination of real and simulated ISP latency and packet loss events. Our binary classification (i.e. classes 'OK' or 'lag') 10-fold cross validation F1 scores are between 0.80 and 0.93 depending on application type. Our multi-class classification (i.e. classes representing discrete packet loss or latency ranges) 10-fold cross validation F1 scores for Minecraft are 0.89 for latency and 0.90 for packet loss. With new business models between ISP's and application developers being actively considered this work represents a significant contribution to the debate by providing scientific evidence relating to a novel approach to scalable QoS measurement
classification, ip traffic, qos, voip, video streaming, gaming
1-18
Middleton, Stuart
404b62ba-d77e-476b-9775-32645b04473f
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Middleton, Stuart
404b62ba-d77e-476b-9775-32645b04473f
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78

Middleton, Stuart and Modafferi, Stefano (2016) Scalable classification of QoS for real-time interactive applications from IP traffic measurements. Computer Networks, 107, 1-18. (doi:10.1016/j.comnet.2016.04.017).

Record type: Article

Abstract

Measurement of network Quality of Service (QoS) has attracted considerable research effort over the last two decades. The recent trend towards Internet Service Providers (ISP's) offering application-specific QoS is creating possibilities for more sophisticated QoS metrics to be offered by ISP's in service level agreements. This in turn could be used for the purposes of improved network optimization and billing according to application specific QoS guarantees. We report a scalable near real-time approach using passively logging IP traffic data for classification of application latency and packet loss across a range of real-time interactive applications. We run six experiments involving Minecraft, Quake 3 Urban Terror, VLC video streaming and the commercial Wirofon VOIP application. We use a mixture of laboratory and real-world deployments, with run times ranging from hours to days, and observe a combination of real and simulated ISP latency and packet loss events. Our binary classification (i.e. classes 'OK' or 'lag') 10-fold cross validation F1 scores are between 0.80 and 0.93 depending on application type. Our multi-class classification (i.e. classes representing discrete packet loss or latency ranges) 10-fold cross validation F1 scores for Minecraft are 0.89 for latency and 0.90 for packet loss. With new business models between ISP's and application developers being actively considered this work represents a significant contribution to the debate by providing scientific evidence relating to a novel approach to scalable QoS measurement

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More information

Accepted/In Press date: 21 April 2016
e-pub ahead of print date: 25 April 2016
Published date: 9 October 2016
Keywords: classification, ip traffic, qos, voip, video streaming, gaming
Organisations: IT Innovation

Identifiers

Local EPrints ID: 393441
URI: http://eprints.soton.ac.uk/id/eprint/393441
PURE UUID: 365a1851-6e0d-45cd-a8f5-986a2a944891
ORCID for Stuart Middleton: ORCID iD orcid.org/0000-0001-8305-8176

Catalogue record

Date deposited: 27 Apr 2016 09:27
Last modified: 03 Dec 2019 06:44

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Contributors

Author: Stuart Middleton ORCID iD
Author: Stefano Modafferi

University divisions

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