Robust resource allocation in a massive multiplayer online gaming environment

  • Authors:

  • Luis Diego Briceño;Howard Jay Siegel;Anthony A. Maciejewski;Ye Hong;Brad Lock;Mohammad Nayeem Teli;Fadi Wedyan;Charles Panaccione;Chris Klumph;Kody Willman;Chen Zhang

  • Affiliations:

  • Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO

  • Venue:
  • Proceedings of the 4th International Conference on Foundations of Digital Games
  • Year:
  • 2009

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Abstract

The environment considered in this research is a massive multiplayer online gaming (MMOG) environment. Each user controls an avatar (an image that represents and is manipulated by a user) in a virtual world and interacts with other users. An important aspect of MMOG is maintaining a fair environment among users (i.e., not give an unfair advantage to users with faster connections or more powerful computers). The experience (either positive or negative) the user has with the MMOG environment is dependent on how quickly the game world responds to the user's actions. This study focuses on scaling the system based on demand, while maintaining an environment that guarantees fairness. Consider an environment where there is a main server (MS) that controls the state of the virtual world. If the performance falls below acceptable standards, the MS can off-load calculations to secondary servers (SSs). An SS is a user's computer that is converted into a server. Four heuristics are proposed for determining the number of SSs, which users are converted to SSs, and how users are assigned to the SSs and the MS. The goal of the heuristics is to provide a "fair" environment for all the users, and to be "robust" against the uncertainty of the number of new players that may join a given system configuration. The heuristics are evaluated and compared by simulation.