Matrix: adaptive middleware for distributed multiplayer games

  • Authors:
  • Rajesh Krishna Balan;Maria Ebling;Paul Castro;Archan Misra

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;IBM Research Watson, Hawthorne, NY;IBM Research Watson, Hawthorne, NY;IBM Research Watson, Hawthorne, NY

  • Venue:
  • Middleware'05 Proceedings of the ACM/IFIP/USENIX 6th international conference on Middleware
  • Year:
  • 2005

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Abstract

Building a distributed middleware infrastructure that provides the low latency required for massively multiplayer games while still maintaining consistency is non-trivial. Previous attempts have used static partitioning or client-based peer-to-peer techniques that do not scale well to a large number of players, perform poorly under dynamic workloads or hotspots, and impose significant programming burdens on game developers. We show that it is possible to build a scalable distributed system, called Matrix, that is easily usable by game developers. We show experimentally that Matrix provides good performance, especially when hotspots occur.