Automated network games enhancement layer

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Automated network games enhancement layer: a proposed architecture

Full text

Pdf (403 KB)

Source

Network and System Support for Games archive
Proceedings of 5th ACM SIGCOMM workshop on Network and system support for games table of contents

Singapore

SESSION: Synchronization, QoS and monitoring in games table of contents

Article No. 9

Year of Publication: 2006

ISBN:1-59593-589-4

Authors

Jason But	Swinburne University of Technology, Melbourne, Australia
Nigel Williams	Swinburne University of Technology, Melbourne, Australia
Sebastian Zander	Swinburne University of Technology, Melbourne, Australia
Lawrence Stewart	Swinburne University of Technology, Melbourne, Australia
Grenville Armitage	Swinburne University of Technology, Melbourne, Australia

Sponsor

SIGCOMM: ACM Special Interest Group on Data Communication

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 3, Downloads (12 Months): 72, Citation Count: 1

Additional Information:

abstract references cited by index terms collaborative colleagues

Tools and Actions:	Request Permissions Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/1230040.1230073 What is a DOI?

ABSTRACT

In this paper we present the design of the Automated Network Games Enhancement Layer (ANGEL), a novel architecture for meeting Quality of Service (QoS) requirements of real-time network game traffic across consumer broadband links. Consumer access links can become bottlenecks when faced with heterogeneous network traffic (e.g. simultaneous use of online games and peer-to-peer file sharing) and the online gaming experience can be significantly affected by bottleneck queuing. Implementing QoS on these links provides improvement by reducing latency and jitter. In our approach network servers automatically identify traffic that might benefit from QoS and then trigger provisioning of QoS by signaling network elements such as access routers. By placing intelligence within the network, QoS decisions can be transparently made for the game applications without imposing an additional processing cost at the access link router. Our system uniquely uses machine learning methods to perform traffic classification.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	ANGEL - Automated Network Games Enhancement Layer, Smart Internet CRC, July 2006. http://caia.swin.edu.au/sitcrc/staticpages/index.php?page=angel.
	2	BART - Broadband Access Research Testbed, Centre for Advanced Internet Architectures - Swinburne University, July 2006. http://caia.swin.edu.au/bart.
	3	IPerf - The TCP/UDP Bandwidth Measurement Tool, July 2006. http://dast.nlanr.net/Projects/Iperf.
	4	A. McGregor, M. Hall, P. Lorier, J. Brunskill. Flow Clustering Using Machine Learning Techniques. In Passive & Active Measurement Workshop, April 2004.
	5	Andrew W. Moore , Denis Zuev, Internet traffic classification using bayesian analysis techniques, Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, June 06-10, 2005, Banff, Alberta, Canada
	6	S. Blake , D. Black , M. Carlson , E. Davies , Z. Wang , W. Weiss, An Architecture for Differentiated Service, RFC Editor, 1998
	7	R. Braden , D. Clark , S. Shenker, Integrated Services in the Internet Architecture: an Overview, RFC Editor, 1994
	8	R. Braden , L. Zhang , S. Berson , S. Herzog , S. Jamin, Resource ReSerVation Protocol (RSVP) -- Version 1 Functional Specification, RFC Editor, 1997
	9	D-Link. 108G Gaming Router. http://games.dlink.com/products/?pid=370.
	10	G. Armitage, Networking and Online Games, John Wiley & Sons, 2006
	11	G. J. Armitage. An Experimental Estimation of Latency Sensitivity in Multiplayer Quake3. In Proceedings 11th IEEE International Conference on Networks (ICON), September 2003.
	12	Sharad Jaiswal , Gianluca Iannaccone , Christophe Diot , Jim Kurose , Don Towsley, Measurement and classification of out-of-sequence packets in a tier-1 IP backbone, Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment, November 06-08, 2002, Marseille, France [doi>10.1145/637201.637218]
	13	L. Stewart, G. Armitage, P. Branch, S. Zander. An Architecture for Automated Network Control of QoS over Consumer Broadband Links. In Poster Presentation at IEEE TENCON, November 2005.
	14	Matthias Dick , Oliver Wellnitz , Lars Wolf, Analysis of factors affecting players' performance and perception in multiplayer games, Proceedings of 4th ACM SIGCOMM workshop on Network and system support for games, October 10-11, 2005, Hawthorne, NY [doi>10.1145/1103599.1103624]
	15	N. Williams, S. Zander, G. Armitage. Evaluating Machine Learning Algorithms for Automated Network Application Identification. Technical Report 060410B, CAIA, April 2006. http://caia.swin.edu.au/reports/060410B/CAIA-TR-060410B.pdf.
	16	N. Williams, S. Zander, G. Armitage. Evaluating Machine Learning Methods for Online Game Traffic Identification. Technical Report 060410C, CAIA, April 2006. http://caia.swin.edu.au/reports/060410C/CAIA-TR-060410C.pdf.
	17	S. Zander. Misclassification of Game Traffic based on Port Numbers: A Case Study using Enemy Territory. Technical Report 060410D, CAIA, April 2006. http://caia.swin.edu.au/reports/060410D/CAIA-TR-060410D.pdf.
	18	Sebastian Zander , David Kennedy , Grenville Armitage, Dissecting server-discovery traffic patterns generated by multiplayer first person shooter games, Proceedings of 4th ACM SIGCOMM workshop on Network and system support for games, October 10-11, 2005, Hawthorne, NY [doi>10.1145/1103599.1103620]
	19	S. Zander, G. Armitage. Empirically Measuring the QoS Sensitivity of Interactive Online Game Players. In Proceedings of Australian Telecommunications and Network Applications Conference (ATNAC), December 2004.
	20	Sebastian Zander , Thuy Nguyen , Grenville Armitage, Automated Traffic Classification and Application Identification using Machine Learning, Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary, p.250-257, November 15-17, 2005 [doi>10.1109/LCN.2005.35]
	21	Tom Beigbeder , Rory Coughlan , Corey Lusher , John Plunkett , Emmanuel Agu , Mark Claypool, The effects of loss and latency on user performance in unreal tournament 2003®, Proceedings of 3rd ACM SIGCOMM workshop on Network and system support for games, August 30-30, 2004, Portland, Oregon, USA [doi>10.1145/1016540.1016556]
	22	Tristan Henderson , Saleem Bhatti, Networked games: a QoS-sensitive application for QoS-insensitive users?, Proceedings of the ACM SIGCOMM workshop on Revisiting IP QoS: What have we learned, why do we care?, August 25-27, 2003, Karlsruhe, Germany [doi>10.1145/944592.944601]
	23	Thomas M. Mitchell, Machine Learning, McGraw-Hill Higher Education, 1997
	24	T. T. T. Nguyen and G. Armitage. Experimentally derived interactions between TCP traffic and service quality over DOCSIS cable links. In Global Internet and Next Generation Networks Symposium, IEEE Globecomm 2004, November 2004.
	25	Ubicom Inc. Solving Performance Problems with Interactive Applications in a Broadband Environment using StreamEngine Technology, October 2004.