Analysis And Application Of Player Behaviors In Network Games

In the recent years, with the developmet of computer network, network games play a very important role in network entertainment. Network games have become a relatively new and independent subject rising from the networking research area, which also becomes one of the main focuses of the research community, the network game service providers and the network game production providers. As the network games have kept growing in terms of both the scales of players and the amount of applications, more and more efforts have been put into getting better game experience without imposing much burden on game servers. By analysing behaviors of players, game providers and players can get the characteristics of game players to improve the game experience and game security,etc.This dissertation covers a series of research on characterizing and analyzing network games and extracting the player behaviors basic information from real data collected from the Internet. From the analysis of player behaviors:We fully analyze behaviors of players during their playing time. We collect the traces of player behaviors in LAN game: CrazyTank, and get the characteristics of habitual behaviors of players. Finally, we propose a new method of path prediction by applying habitual behaviors of players.We are the first to propose a reasonable method to prevent in-game cheats. We compile a plug-in software to collect player data in MMORPG World of Warcraft from game client. We analyse the correlationship of players and get the relationship map of the whole players in the game server. We draw credit degree into our method, and we think credit degree can transmit; finally we use these mechanisms to help players to prevent in-game cheats. From the analysis of game virtual environment effectionWe are the first to propose a solution named Interest Scheme (IS) to achieve much more path prediction accuracy in network games when network latency is unsteady and package loss is frequent. IS assumes that path prediction of a given player has relations to its nearby objects and players in game space. In IS, the surroundings of a given entity is taken into account in path prediction. Moreover, we consider that different prediction method should be used for different network latency. So, a hybrid method, which is a combination of IS and traditional method, is introduced. Simulation shows that our method achieves significant improvement in path prediction.We are the first to propose a method to evaluate latency of players from local client according to reaction of players and rules of the game system. In network games, because of network delay, two players can hardly see each other at the same time, though they have the same range of visual scope. From the view of local client, The movement of a nearby player looks like to be made sooner or later, and so is the nearby player. So, reaction of the nearby player to the movement of the local player will occur at different time from local view, when he is under different network condition. We can evaluate the latency of clients by the distinction of reaction time. Simulation shows that our method achieves significant accuracy in latency evaluation.