A Stochastic Model of Plausibility in Live-Virtual-Constructive Environments

Distributed live-virtual-constructive simulation promises a number of benefits for the test and evaluation community, including reduced costs, access to simulations of limited availability assets, the ability to conduct large-scale multi-service test events, and recapitalization of existing simulation investments. However, geographically distributed systems are subject to fundamental state consistency limitations that make assessing the data quality of live-virtual-constructive experiments difficult. This research presents a data quality model based on the notion of plausible interaction outcomes. This model explicitly accounts for the lack of absolute state consistency in distributed real-time systems and offers system designers a means of estimating data quality and fitness for purpose. Experiments with World of Warcraft player trace data validate the plausibility model and exceedance probability estimates. Additional experiments with synthetic data illustrate the model\u27s use in ensuring fitness for purpose of live-virtual-constructive simulations and estimating the quality of data obtained from live-virtual-constructive experiments

Approximation Algorithm for Estimating Distances in Distributed Virtual Environments

International audienceThis article deals with the issue of guaranteeing properties in Distributed Virtual Environments (DVEs) without a server and without global knowledge of the system state and therefore only by exchanging messages. This issue is particularly relevant in the case of online games, that operate in a fully distributed framework and for which network resources such as bandwidth are the critical resources. In the context of games, players typically need to know the distance between their character and other characters, at least approximately. Players all share the same position estimation algorithm but, in general, do not know the current positions of others. We provide a synchronized distributed algorithm Alc to guarantee, at any time, that the estimated distance d est between any pair of characters A and B is always a 1 + ε approximation of the current distance d act. Our result is twofold: (1) we prove that if characters move randomly on a d-dimensional grid, or follow a random continuous movement on up to three dimensions, the number of messages of Alc is optimal up to a constant factor; (2) in a more practical setting, we also observe that the number of messages of Alc for actual game traces is much less than the standard algorithm sending actual positions at a given frequency

Cheating Prevention in Peer-to-Peer-based Massively Multiuser Virtual Environments

Massively multiuser virtual environments (MMVEs) have become an increasingly popular Internet application in recent years. Until now, they are all based on client/server technology. Due to its inherent lack of scalability, realizing MMVEs based on peer-to-peer technology has received a lot of interest. From the perspective of the operator, using peer-to-peer technology raises additional challenges: the lack of trust in peers and their unreliability. The simulation of the virtual environment is governed by certain rules specified by the operator. These rules state what actions can be taken by users in the virtual environment and how the state of the environment changes based on these actions. Since MMVEs are very often competitive environments, some people will cheat and try to break the rules to get an unfair advantage over others. Using a central server performing the simulation of the virtual environment, the operator can ensure only allowed actions can be performed and the state of the environment evolves according to the rules. In a peer-to-peer setting, the operator has no control over the peers so they might not behave as implemented by the operator. Furthermore, a central server is inherently more reliable than a peer which could fail at any time so data might be lost. This thesis presents the design of a storage performing a distributed simulation of a virtual environment. It uses a deterministic event-based simulation to calculate the state of the virtual environment only based on the actions of its users. There are multiple replicated simulations using a voting mechanism to overcome the influence of malicious peers trying to tamper with the state of the environment as long as the number of malicious peers does not reach a critical threshold. Replication of data also ensures data is not lost when peers fail. The storage is based on a peer-to-peer overlay allowing peers to exchange messages to store and retrieve data. It creates a Delaunay graph structure matching the way the data in the virtual environment is distributed among the peers. A self-stabilizing algorithm keeps the structure intact as peers join and leave the network. Additional routing tables allow peers to retrieve stored replicas independently on short, disjoint paths reducing the influence of malicious peers on the retrieval of data. A redundant filling algorithm prevents malicious peers from tampering with these routing tables to get more messages routed their way