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On-line gaming is an increasingly popular form of entertainment on the Internet, with the on-line market predicted to be worth over $5 billion dollars in 2008 [1]. As an example of a popular, money-making game, EverQuest [2] has over 450,000 subscribers each paying a monthly fee and purchasing two yearly expansions. Unfortunately for game companies, the success of a game is highly unpredictable. To make matters worse, there are substantial costs in developing and hosting on-line games. As a result, such companies are increasingly exploring shared, on-line hosting platforms such as on-demand computing infrastructure provided by companies such as IBM and HP [3,4,5,6,7,8,9,10].

In order to judge the feasibility of such an approach, it is important for game and hosting companies to understand how gamers and game workloads behave. Knowing the behavior of players, the predictability of workloads, and the potential for resource sharing between applications allows infrastructure to be tailored to the needs of games. While there has been a substantial amount of work characterizing web and peer-to-peer users and workloads [11,12], there is very little known about game players and workloads.

In order to provide insight into such issues, this paper examines several large traces of aggregate player populations of a collection of popular games as well as the individual player population of a busy game server. We present a detailed analysis of on-line game players and workloads that targets several key areas which are important to game and hosting providers including:

Section 2 describes the methodology behind our study. Section 3 analyzes properties of individual gamers. Section 4 describes trends of on-line gaming in aggregate. Section 5 evaluates the potential for multiplexing games and web traffic together, and Section 6 discusses our conclusions.

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