We collected mobility traces of 84,208 avatars spanning 22 regions over two months in Second Life, a popular networked virtual environment. We analyzed the traces to characterize the dynamics of the avatars mobility and behavior, both temporally and spatially. We discuss the implications of the our findings to the design o f peer-to-peer networked virtual environments, interest management, mobility modeling of avatars, server load balancing and zone partitioning, client-side caching, and prefetching.
@cite_5 and @cite_26 collected traces from Quake III, a popular, multi-player, first person shooting (FPS) game and developed mobility models to describe the movement of the players. @cite_3 collected a large trace, comparable in scale to ours, of players movement from World of Warcraft (WoW), a massively multi-player online role playing game (MMORPG), and analyzed the dynamics of the populations, players arrival departure rate, session length, player distribution, and player movements. FPS games and MMORPGs have different characteristics than NVEs. Players in fast-action, FPS games tend to move around constantly. In MMORPGs, players usually engage in quests to gain level and new abilities. Players tend to gather in a location for an event (e.g. new monsters to fight) and disperse afterwards. Players also tend to move in groups. We observed a different pattern for NVEs.
@cite_5 @cite_26 @cite_3
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We consider multi-player repeated games involving a large number of players with large strategy spaces and enmeshed utility structures. In these ldquolarge-scalerdquo games, players are inherently faced with limitations in both their observational and computational capabilities. Accordingly, players in large-scale games need to make their decisions using algorithms that accommodate limitations in information gathering and processing. This disqualifies some of the well known decision making models such as ldquoFictitious Playrdquo (FP), in which each player must monitor the individual actions of every other player and must optimize over a high dimensional probability space. We will show that Joint Strategy Fictitious Play (JSFP), a close variant of FP, alleviates both the informational and computational burden of FP. Furthermore, we introduce JSFP with inertia, i.e., a probabilistic reluctance to change strategies, and establish the convergence to a pure Nash equilibrium in all generalized ordinal potential games in both cases of averaged or exponentially discounted historical data. We illustrate JSFP with inertia on the specific class of congestion games, a subset of generalized ordinal potential games. In particular, we illustrate the main results on a distributed traffic routing problem and derive tolling procedures that can lead to optimized total traffic congestion. Understanding the distributions and behaviors of players within Massively Multiplayer Online Games (MMOGs) is essential for research in scalable architectures for these systems. We provide the first look into this problem through a measurement study on one of the most popular MMOGs, World of Warcraft [15]. Our goal is to answer four fundamental questions: how does the population of the virtual world change over time, how are players distributed in the virtual world, how much churn occurs with players, and how do they move in the virtual world. Through probing-based measurements, our preliminary results show that populations fluctuate according to a prime-time schedule, player distribution and churn appears to occur on a power-law distribution, and players move to only a small number of zones during each playing session. The ultimate goal of our research is to design an accurate player model for MMOGs so that future research can predict and simulate player behavior and population fluctuations over time. This paper proposes the Networked Game Mobility Model (NGMM), for synthesising mobility in First-Person-Shooter (FPS) networked games. Current networked game research focuses on modelling low-level aspects, such as packet inter-arrival times and packet sizes, to optimise network traffic and efficient use of gaming servers. Due to the increasing popularity of multiplayer online games, the need has arisen to develop more realistic models. NGMM is such a model that utilises application level aspects of networked game traces to statistically model FPS games. It is believed that an understanding of the application level aspect (e.g. mobility and user actions) of the network is necessary to derive the causality of increasing workloads on the servers, particularly in response to increasing online game popularity. To evaluate the performance of the model simulations, comparisons are made between the original game traces, the Random Way Point Model and NGMM. Analyses of the comparative simulation results show that NGMM is capable of closely matching actual game traces. The incorporation of application level knowledge, performance boundaries of current optimisation techniques, including dead-reckoning and interest management, are also effectively ascertained in this research. This is particularly significant as current models are unable to evaluate their impact with optimisation techniques. Massively Multiplayer Online Games (MMOGs) routinely attract millions of players but little empirical data is available to assess their players' social experiences. In this paper, we use longitudinal data collected directly from the game to examine play and grouping patterns in one of the largest MMOGs: World of Warcraft. Our observations show that the prevalence and extent of social activities in MMOGs might have been previously over-estimated, and that gaming communities face important challenges affecting their cohesion and eventual longevity. We discuss the implications of our findings for the design of future games and other online social spaces.