Table of Contents Author Guidelines Submit a Manuscript
International Journal of Computer Games Technology
Volume 2014, Article ID 138596, 18 pages
http://dx.doi.org/10.1155/2014/138596
Research Article

Dead Reckoning Using Play Patterns in a Simple 2D Multiplayer Online Game

1Faculty of Business and I.T., University of Ontario Institute of Technology, Oshawa, ON, Canada L1H 7K4
2School of Computer Science, Carleton University, Ottawa, ON, Canada K1S 5B6

Received 5 January 2014; Revised 27 March 2014; Accepted 1 April 2014; Published 12 May 2014

Academic Editor: Abdennour El Rhalibi

Copyright © 2014 Wei Shi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In today’s gaming world, a player expects the same play experience whether playing on a local network or online with many geographically distant players on congested networks. Because of delay and loss, there may be discrepancies in the simulated environment from player to player, likely resulting in incorrect perception of events. It is desirable to develop methods that minimize this problem. Dead reckoning is one such method. Traditional dead reckoning schemes typically predict a player’s position linearly by assuming players move with constant force or velocity. In this paper, we consider team-based 2D online action games. In such games, player movement is rarely linear. Consequently, we implemented such a game to act as a test harness we used to collect a large amount of data from playing sessions involving a large number of experienced players. From analyzing this data, we identified play patterns, which we used to create three dead reckoning algorithms. We then used an extensive set of simulations to compare our algorithms with the IEEE standard dead reckoning algorithm and with the recent “Interest Scheme” algorithm. Our results are promising especially with respect to the average export error and the number of hits.