Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Tigers vs Lions: Towards Characterizing Solitary and Group User Behavior in MMORPG

The development of Internet technologies enables software developers to build virtual worlds such as Massively Multi-Player Online Role-Playing Games (MMORPGs). The population of such games shows super-linear growing tendency. It is estimated that the number of Internet users subscribed in MMORPGs is more than 22 million worldwide [1]. However, only little is known about the characteristics of traffic generated by such games as well as the behavior of their subscribers. In this paper, we characterize the traffic behavior of World of Warcraft, the most subscribed MMORPG in the world, by analyzing Internet traffic data sets collected from a European tier-1 ISP in two different time periods. We find that World of Warcraft is an influential application regarding the time spent by users (1.76 and 4.17 Hours/day on average in our measurement), while its traffic share is comparatively low (< 1%). In this respect, we look at the World of Warcraft subscriber’s gaming behavior by categorizing them into two different types of users (solitary users and group users) and compare these two groups in relation to the playing behavior (duration as the metric) and the in-game behavior (distance as the metric)

Information fusion architectures for security and resource management in cyber physical systems

Data acquisition through sensors is very crucial in determining the operability of the observed physical entity. Cyber Physical Systems (CPSs) are an example of distributed systems where sensors embedded into the physical system are used in sensing and data acquisition. CPSs are a collaboration between the physical and the computational cyber components. The control decisions sent back to the actuators on the physical components from the computational cyber components closes the feedback loop of the CPS. Since, this feedback is solely based on the data collected through the embedded sensors, information acquisition from the data plays an extremely vital role in determining the operational stability of the CPS. Data collection process may be hindered by disturbances such as system faults, noise and security attacks. Hence, simple data acquisition techniques will not suffice as accurate system representation cannot be obtained. Therefore, more powerful methods of inferring information from collected data such as Information Fusion have to be used. Information fusion is analogous to the cognitive process used by humans to integrate data continuously from their senses to make inferences about their environment. Data from the sensors is combined using techniques drawn from several disciplines such as Adaptive Filtering, Machine Learning and Pattern Recognition. Decisions made from such combination of data form the crux of information fusion and differentiates it from a flat structured data aggregation. In this dissertation, multi-layered information fusion models are used to develop automated decision making architectures to service security and resource management requirements in Cyber Physical Systems --Abstract, page iv