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Video Game Traffic Profile. Glenn Harper Joseph Sanchez Everett Espinoza Anthony Baros. Video Gaming: A Burgeoning Industry. As of 2002, Video Gaming was a $30 Billion per year industry. Game sales rival CD, DVD, and Box Office sales. Example: Sony Playstation 2
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Video Game Traffic Profile Glenn Harper Joseph Sanchez Everett Espinoza Anthony Baros
Video Gaming: A Burgeoning Industry • As of 2002, Video Gaming was a $30 Billion per year industry. • Game sales rival CD, DVD, and Box Office sales. • Example: Sony Playstation 2 • 25 million consoles sold, 2.6 million connected (with separate adapter).
Online Gaming: The Next Big Thing • SCEA study has noted that the peak time for online play is between 5 and 11 pm • Nielsen (Television ratings) has noted a drop in the number of viewers among males 18-24 during the same time period. • The rise of online gaming and video gaming has had a huge impact on entertainment landscape.
Previous Work • Many previous studies have been done to measure Web or Multimedia traffic • Game traffic should be different: Low latency, small packet size, bursty traffic
A Challenge to the Existing Infrastructure of the Internet • Large amount of users requires a relatively high bandwidth, massively scalable method of connecting to servers. • How do gaming developers and system administrators meet this need?
Profiling Traffic from Online Gaming Three focuses for our project: • What type of traffic is used to connect between clients and servers? • How many gamers are connecting, and how does the number change throughout the day? • What is the geographic distribution of online gamers?
Possible benefits of this study • Good data will allow the design of networks to better accommodate network gaming traffic “turbulence” • Provide data for more realistic network simulations
Type of Traffic • Hypothesis: mostly UDP, with TCP connection to tell server when clients join and disconnect. • Tested using network connection monitoring tool while observing an online game.
Number of Gamers • Hypothesis: Absolute number unknown, but peak should be between 5 and 11 pm, as per the SCEA study. • Test by looking at the number of gamers on “closest” servers at various times during the day.
Geographic Distribution • Hypothesis: Should see a normal distribution on a map of the Southwestern USA. • Means should be at cities (Albuquerque, Phoenix, San Antonio, Denver, etc.) • Test by taking IPs of servers with low lag, then plug those IPs into a location finder.
Initially set up server, but no one connected. • Initially set up server, but no one connected. Took different approach: • Looked at servers with latency < 50, and servers located in southwest • Assumed these would be servers connecting to us.
Testing results for span of two weeks for • Number of Players • Number of Active servers • Types of network connections occuring during gaming • Locations of various servers
Results for individual days of the week: • Number of players • Number of active servers
Mechanism for determining types of gaming connections: Used Netmon 1.1, which records the following: • Remote Address • Local address • Port number used • Type of protocol used
This software allowed us to determine the various types of connections utilized throughout game play
Types of connections determined: • There are TCP Connections to central Steam server. These connections perform basic control functions • Majority connection types are UDP, which contain the bulk of the data. UDP connection is the basic server-client connection.
Geographic Distribution http://ws.arin.net/ was used to find out the organization which a IP address belonged to and thus the location of the server’s city
Sample Data: OrgName: Game Daemons, Inc. OrgID: GAMED Address: P.O. Box 702 City: Midway StateProv: UT PostalCode: 84909 Country: US NetRange: 69.12.8.0 - 69.12.9.255 OrgName: Cyberbasin Internet Services OrgID: CIS-218 Address: 407 N Big Spring City: Midland StateProv: TX PostalCode: 79702 Country: US NetRange:65.164.136.0 - 65.164.139.255
After looking up the location of 50 IP addresses, this is the distribution:
Conclusions • Network games different than typical Internet applications • Very Interactive • Traffic flow profile consists mainly of small bursts of UDP packets • For Counter-strike game, we see burstier data rate depending upon action • Packet sizes for server depend upon action