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Network Game Research – Introduction and Counter-strike Analysis

Network Game Research – Introduction and Counter-strike Analysis. Mark Claypool. Outline. Overview of Network Games Net Games Conference Research Issues Analysis Counter-strike Our Results. Why Study Games?. Rapidly increasing in popularity Forrester Research: 18 million on-line in 2001

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Network Game Research – Introduction and Counter-strike Analysis

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  1. Network Game Research –Introduction and Counter-strike Analysis Mark Claypool

  2. Outline • Overview of Network Games • Net Games Conference • Research Issues • Analysis Counter-strike • Our Results

  3. Why Study Games? • Rapidly increasing in popularity • Forrester Research: 18 million on-line in 2001 • Consoles on-line • Playstation 2 on-line (9/2002) • Xbox Live (12/2002) • Cell phones • Doom port (Nokia) • Design networks to better accommodate traffic

  4. Game Types • First Person Shooters • Doom, Quake, Counter-strike, … • Massive Multi-Player Online Role Playing • Everquest, Earth and Beyond, … • Real-Time Strategy • Warcraft, Starcraft … • Other • Misc – not any genre above • Example: Diablo2, Racing, … • Non-networked • Example: Thief • Multiplayer, but relaxed real time • Example: Chess, Bridge

  5. Net-Games - Workshop on Network and System Support for Games • First was 2002 in Braunschweig, Germany • http://wwwmc.tm.uni-karlsruhe.de/netgames2002/ • Second is in Redwood City, California • http://confman.eecs.umich.edu/netgames2003/ • Sponsored by: • ACM • Electronic Arts • Microsoft

  6. Net-Games Program Committee • Sugih Jamin, University of Michigan (Chair) • Mostafa Ammar, Georgia Institute of Technology • Grenville Armitage, Swinburne University of Technology • John Buchanan, Electronic Arts • Jon Crowcroft, University of Cambridge • Christophe Diot, Sprintlabs • Wu-chang Feng, Oregon Health and Science University • Carsten Griwodz, University of Oslo • Jim Kurose, UMass at Amherst • John Laird, University of Michigan • Brian Neil Levine, UMass at Amherst • Martin Mauve, University of Mannheim • Hiroyuki Morikawa, University of Tokyo • Dan Rubenstein, Columbia University • Srinivasan Seshan, Carnegie Mellon University • Wilson Yuen, City University of Hong Kong • Lars Wolf, TU Braunschweig

  7. Net-Games Topics • Multi-player game architectures and platforms • Prevention and detection of cheating • Games on mobile and resource-scarce devices • AI and techniques for latency hiding • Modeling, usage studies, and characterization • Enabling protocols for networked games • Systems support for authentication and accounting • Put research issues here

  8. Wu-chang Feng, Francis Chang, Wu-chi Feng, Jonathan Walpole Provisioning On-line Games: A Traffic Analysis of a Busy Counter-Strike Server

  9. Goal • Understand the resource requirements of a popular on-line FPS (first-person shooter) game

  10. Why FPS? • While there are other game types … • Gaming traffic dominated by first-person shooter genre (FPS) [McCreary00]

  11. Networked FPS lineage Doom Unreal Unreal Tournament Doom II Quake + QuakeWorld variants + Team Fortress + Capture the Flag Unreal Tournament 2003 + America's Army: Operations Quake II + Soldier of Fortune + Heretic II Quake III Arena + Medal of Honor Allied Assault + Return to Castle Wolfenstein + Soldier of Fortune 2 + Jedi Knight II Half-Life + Counter-Strike + Day of Defeat + Urban Terror + Team Fortress Classic + Team Fortress 2 8 of top 10 games derived from one of two lineages Doom III

  12. About the game... • Half-Life modification • Two squads of players competing in rounds lasting several minutes • Rounds played on maps that are rotated over time • Each server supports up to 32 players

  13. What is Counter-strike (CS)?

  14. What is Counter-strike (CS)?

  15. What is Counter-strike (CS)?

  16. About the game... • Centralized server implementation • Clients update server with actions from players • Server maintains global information and determines game state • Server broadcasts results to each client • Sources of network traffic • Real-time action and coordinate information • Broadcast in-game text messaging • Broadcast in-game voice messaging • Customized spray images from players • Customized sounds and entire maps from server

  17. Why CS?

  18. Why CS?

  19. The Trace • cs.mshmro.com (129.95.50.147) • Dedicated 1.8GHz Pentium 4 Linux server • OC-3 • 70,000+ unique players (WonIDs) over last 4 months • One week in duration 4/11 – 4/18 • 500 million packets • 16,000+ sessions from 5800+ different players

  20. A week in the life...

  21. Variance time plot Less variance < 50ms Remains to 30 min Decreases above 30 min (Normalized to base interval of 10ms)

  22. Digging deeper • Periodic server bursts every 50ms • Game must support high interactivity • Game logic requires predictable updates to perform lag compensation Interval size=10ms Interval size=50ms

  23. Digging deeper • Low utilization every 30 minutes • Server configured to change maps every 30 minutes • Traffic evenly pegged otherwise.... Interval size=1sec Interval size=30min

  24. Finding the source of predictability • Games must be fair across all mediums (i.e. 56kers) • Aggregate predictability due to “saturation of the narrowest last-mile link”

  25. Packet sizes • Supporting narrow last-mile links with a high degree of interactivity requires small packets • Clients send small single updates • Servers aggregate and broadcast larger global updates

  26. Implications • Routers, firewalls, etc. must be designed to handle large bursts at millisecond levels • Game requirements do not allow for loss or delay (lag) • Should not be provisioned assuming a large average packet size [Partridge98] • If there are buffers anywhere, they must... • Use ECN (no, doesn’t use TCP) • Be short (i.e. not have a bandwidth-delay product of buffering) • Employ an AQM that works with short queues • Rate-based not Queue-based

  27. Implications • ISPs, game services • Must examine “lookup” utilization in addition to link utilization • Concentrated deployments of game servers may be problematic • Large server farms in a single co-lo • America's Army, UT2K3, Xbox

  28. On-going work • Other pieces in the provisioning puzzle • Aggregate player populations • Geographic distributions of players over time (IP2Geo) • Impact on route and packet classification caching • Other FPS games • HL-based: Day of Defeat • UT-based: Unreal Tournament 2003, America's Army • Quake-based: Medal of Honor: Allied Assault • Results apply across other FPS games and corroborated by other studies

  29. Future work • Games as passive measurement infrastructure • Only widespread application with continuous in-band ping information being delivered (measurement for free) • “Ping times” of all clients broadcast to all other clients every 2-3 seconds • 20,000+ servers, millions of clients • Games as active measurement infrastructure • Thriving FPS mod community and tools • Server modifications [Armitage01] • Other game types

  30. Some Net-Games Research at WPI • Mark Claypool, David LaPoint, and Josh Winslow. “Network Analysis of Counter-strike and Starcraft”, In Proceedings of the 22nd IEEE International Performance, Computing, and Communications Conference (IPCCC), Phoenix, Arizona, USA, April 2003. Online at: http://www.cs.wpi.edu/~claypool/papers/net-game/ • Compared FPS (Counter-strike) with RTS (Starcraft) • Smaller number of traces • Controlled set of users

  31. Our Results • Confirms packet sizes for Counter-strike • Starcraft results: • Packets smaller • Linear increase with number of players • Starcraft traffic much smoother (bandwidth usage) than Counter-strike • Counter-strike bursty during ‘fire-fights’ • (PEDS talk later)

  32. Network Game Research –Introduction and Counter-strike Analaysis Mark Claypool

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