We are developing a distributed architecture for massivelymultiplayer games. In this paper, we focus on designing a low-latency event ordering protocol, called NEO, for this architecture. Previous event ordering protocols prevent several types of cheats at the expense of operating at the latency of the slowest player. We broaden the definition of cheating to include four common protocol level cheats and demonstrate how NEO prevents these cheats. At the same time, NEO has a playout latency independent of network conditions and adapts to network congestion to optimize performance.

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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.

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Abstract. Understanding player distributions, sessions, and movements in a Massively Multiplayer Online Role-Playing Game (MMORPG) is essential for research in scalable architectures for these systems. We present the first detailed measurement study and the first models of the virtual populations in two popular MMORPGs, World of Warcraft TM and Warhammer Online TM . Our results show that while these two types of MMORPGs are significantly different in play style, the features of their virtual populations can be modeled similarly, allowing future researchers to accurately simulate these types of games.

Abstract. Pearson product-moment correlation coefficients are a wellpracticed quantification of linear dependence seen across many fields. When calculating a sample-based correlation coefficient, the accuracy of the estimation is dependent on the quality and quantity of the sample. Like all statistical models, these correlation coefficients can suffer from overfitting, which results in the representation of random error instead of an underlying trend. In this paper, we discuss how Pearson product-moment correlation coefficients can utilize information outside of the two items for which the correlation is being computed. By introducing a transitive relationship with one or more additional items that meet specified criterion, our Transitive Pearson product-moment correlation coefficient can significantly reduce the error, up to over 50%, of sparse, sample-based estimations. Finally, we demonstrate that if the data is too dense or too sparse, transitivity is detrimental in reducing the correlation estimation errors.

In many networks, such as mobile ad-hoc networks and friend-to-friend overlay networks, direct communication between nodes is limited to specific neighbors. Often these networks have a small-world topology; while short paths exist between any pair of nodes in small-world networks, it is non-trivial to determine such paths with a distributed algorithm. Recently, Clarke and Sandberg proposed the first decentralized routing algorithm that achieves efficient routing in such small-world networks. This paper is the first independent security analysis of Clarke and Sandberg's routing algorithm. We show that a relatively weak participating adversary can render the overlay ineffective without being detected, resulting in significant data loss due to the resulting load imbalance. We have measured the impact of the attack in a testbed of 800 nodes using minor modifications to Clarke and Sandberg's implementation of their routing algorithm in Freenet. Our experiments show that the attack is highly effective, allowing a small number of malicious nodes to cause rapid loss of data on the entire network.We also discuss various proposed countermeasures designed to detect, thwart or limit the attack. While we were unable to find effective countermeasures, we hope that the presented analysis will be a first step towards the design of secure distributed routing algorithms for restricted-route topologies.