Abstract—For many networked games, such as the Defense of the Ancients and StarCraft series, the unofficial leagues created by players themselves greatly enhance user-experience, and extend the success of each game. Understanding the social structure that players of these games implicitly form helps to create innovative gaming services to the benefit of both players and game operators. But how to extract and analyse the implicit social structure? We address this question by first proposing a formalism consisting of various ways to map interaction to social structure, and apply this to real-world data collected from three different game genres. We analyse the implications of these mappings for in-game and gaming-related services, ranging from network and socially-aware matchmaking of players, to an investigation of social network robustness against player departure. I.

ter verkrijging van de graad van doctor

are an important type of distributed applications and have millions of users. Traditionally, MMOGs are hosted on dedicated clusters, distributed globally. With the advent of cloud computing, MMOGs such as Zynga’s are increasingly run on cloud resources, through the use of cloud technology and innovation. Massivizing MMOGs on clouds is the focus of my PhD research. My main contributions are: 1) analyzing and modeling various MMOG workloads, including those of social and traditional real-time games, 2) designing and implementing a cost-efficient and reliable cloud-based MMOG platform, 3) designing and implementing a scalable MMOG system which employs domain-specific scaling techniques to support the realtime strategy games of the future, 4) experimental prototypes and tools to evaluate our proposed research via real-world experimentation and simulation, and applying our proposed research to a popular real-world application. In this article, I introduce my research progress and my future plans. I.

Abstract—Networks are used in many research domains to model the relationships between entities. We present a publicly available toolkit to extract graphs from datasets or data streams and to analyse their properties. The graph extraction is based on a set of rules that define the links between entities in a set or stream of self-contained events involving sets of entities. As the extracted graph is dynamic and, moreover, can be spread over multiple machines, we include the class of gossip algorithms to analyse them. In addition, the toolkit also contains algorithms to compute metrics of static snapshots of the dynamic graph. I.

Abstract—For many networked games, such as the Defense of the Ancients and StarCraft series, the unofficial leagues created by players themselves greatly enhance user-experience, and extend the success of each game. Un-derstanding the social structure that players of these games implicitly form helps to create innovative gaming services to the benefit of both players and game operators. But how to extract and analyse the implicit social structure? We address this question by first proposing a formalism consisting of various ways to map interaction to social structure, and apply this to real-world data collected from three different game genres. We analyse the implications of these mappings for in-game and gaming-related services, ranging from network and socially-aware matchmaking of players, to an investigation of social network robustness against player departure. I.