Alexandre Denault

Mammoth: a massively multiplayer game research framework

This paper presents Mammoth, a massively multiplayer game research framework designed for experimentation in an academic setting. Mammoth provides a modular architecture where different components, such as the network engine, the replication engine, or interest management, can easily be replaced. Subgames allow a researcher to define different game goals, for instance, in order to evaluate the effects of different team-play tactics on the game performance. Mammoth also offers a modular and flexible infrastructure for the definition of non-player characters with behavior controlled by complex artificial intelligence algorithms. This paper focuses on the Mammoth architecture, demonstrating how good design practices can be used to create a modular framework where researchers from different research domains can conduct their experiments. The effectiveness of the architecture is demonstrated by several successful research projects accomplished using the Mammoth framework.

Persistence in massively multiplayer online games

The most important asset of a Massively Multiplayer Online Game is its world state, as it represents the combined efforts and progress of all its participants. Thus, it is extremely important that this state is not lost in case of server failures. Survival of the world state is typically achieved by making it persistent, e.g., by storing it in a relational database. The main challenge of this approach is to track the large volume of modifications applied to the world in real time. This paper compares a variety of strategies to persist changes of the game world. While critical events must be written synchronously to the persistent storage, a set of approximation strategies are discussed and compared that are suitable for events with low consistency requirements, such as player movements. An analysis to better understand the possible limitations and bottlenecks of these strategies is presented using experimental data from an MMOG research framework. Our analysis shows that a distance-based solution offers the scalability and efficiency required for large-scale games as well as offering error bounds and eliminating unnecessary updates associated with localized movement.

Model-based design of computer-controlled game character behavior

Recently, the complexity of modern, real-time computer games has increased drastically. The need for sophisticated game AI, in particular for Non-Player Characters, grows with the demand for realistic games. Writing consistent, re-useable and efficient AI code has become hard. We demonstrate how modeling game AI at an appropriate abstraction level using an appropriate modeling language has many advantages. A variant of Rhapsody Statecharts is proposed as an appropriate formalism. The Tank Wars game by Electronic Arts (EA) is used to demonstrate our concrete approach. We show how the use of the Statecharts formalism leads quite naturally to layered modeling of game AI and allows modelers to abstract away from choices between, for example, time-slicing and discrete-event time management. Finally, our custom tools are used to synthesize efficient C++ code to insert into the Tank Wars main game loop.

Triangle-based obstacle-aware load balancing for massively multiplayer games

Massively multiplayer games run on large server farms in order to handle the huge load that is caused by the thousands of players that play these games concurrently. Current systems use very simple load-balancing mechanisms restricting the semantics of the game. In this paper, we present a dynamic load balancing mechanism that considers both the load associated with performing game actions as well as the load incurred through interest management. As clients join, they can take on load due to game actions and update notifications. When players flock to some part of the world, our system is able to dynamically redistribute the imbalanced interest management load among servers. This hybrid mechanism is integrated into the Mammoth multiplayer gaming environment and our real-world experiments show how equal load distribution is maintained under changing workloads.

Journey: A Massively Multiplayer Online Game Middleware

The design of massively multiplayer online games (MMOGs) is challenging because scalability, consistency, reliability, and fairness must be achieved while providing good performance and enjoyable gameplay. This article presents Journey, an MMOG middleware that hides the complexity of dealing with the aforementioned issues from the game programmer. Journey builds on top of a peer-to-peer network infrastructure to provide load-balancing, fault-tolerance, and cheat-detection capabilities centered on object-oriented technology. Experimental results show performance measurements obtained by running Journey on more than 200 machines.

The perils of using simulations to evaluate Massively Multiplayer Online Game performance

To test and benchmark Massively Multiplayer Online Games (MMOGs) requires hundreds, if not thousands of human players. Given this impracticality, many researchers substitute experimentation with simulation. However, when investigating performance and scalability issues, simulated experiments often yield results that heavily depend on the experimental setup. This paper critically reflects on the use of simulation to conduct experiments in MMOGs. Using Mammoth, a MMOGs research framework, performance measurements such as CPU usage, memory usage and used network bandwidth are collected while running the same game scenario using five different simulation setups. The results are analyzed, and the discovered differences are discussed. The paper concludes that experiments which are aimed at measuring the performance of a MMOGs using simulations must be designed very carefully, especially if they are run on a single machine.

Avoid common pitfalls when programming 2D graphics in java: lessons learnt from implementing the minueto toolkit

This paper presents the core knowledge required to properly develop 2D games in Java. We describe the common pitfalls that can easily degrade graphics performance and show how we achieved impressive frames-per-second display updates when implementing Minueto, a game development framework.

Be a computer scientist for a week the McGill “game programming guru” Summer Camp

Motivating high school students to consider Computer Science as their future field of study at the university level is a challenging endeavor. This paper describes the McGill computer science summer camp targeted at high school students from grade 10 to 11 (ages 15 to 17). We first motivate our choice of using computer games as the main camp theme, and then present the teaching methodology used throughout the camp. A day-by-day breakdown of the camp is provided, as to better illustrate the distribution of the material throughout the week and the evaluation methods used to track the progress of the students. We also present the game environment we developed in which the students exercise their problem solving skills during the lab sessions. We conclude by illustrating the positive effect of the camp, using a combination of code analysis and evaluation questionnaire filled out by the students and their parents.