ERA

Download the full-sized PDF of Dynamically learning efficient server/client network protocols for networked simulationsDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R3JG6X

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Graduate Studies and Research, Faculty of

Collections

This file is in the following collections:

Theses and Dissertations

Dynamically learning efficient server/client network protocols for networked simulations Open Access

Descriptions

Other title
Subject/Keyword
networking
games
software engineering
compression
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Orsten, Sterling
Supervisor and department
Buro, Michael (Computing Science)
Examining committee member and department
Nikolaidis, Ioanis (Computing Science)
Ardakani, Masoud (Electrical and Computer Engineering)
Department
Department of Computing Science
Specialization

Date accepted
2011-01-26T21:25:41Z
Graduation date
2011-06
Degree
Master of Science
Degree level
Master's
Abstract
With the rise of services like Steam and Xbox Live, multiplayer support has become essential to the success of many commercial video games. Explicit, server-client synchronisation models are bandwidth intensive and error prone to implement, while implicit, peer-to-peer synchronisation models are brittle, inflexible, and vulnerable to cheating. We present a generalised server-client network synchronisation model targeted at complex games, such as real time strategy games, that previously have only been feasible via peer-to-peer techniques. We use prediction, learning, and entropy coding techniques to learn a bandwidth-efficient incremental game state representation while guaranteeing both correctness of synchronised data and robustness in the face of unreliable network behavior. The resulting algorithms are efficient enough to synchronise the state of real time strategy games such as Blizzard’s Starcraft (which can involve hundreds of in-game characters) using less than three kilobytes per second of bandwidth.
Language
English
DOI
doi:10.7939/R3JG6X
Rights
License granted by Sterling Orsten (sorsten@ualberta.ca) on 2011-01-25 (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication

File Details

Date Uploaded
Date Modified
2014-04-29T21:17:27.502+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 1188636
Last modified: 2015:10:12 19:56:55-06:00
Filename: sterling_orsten_msc_thesis.pdf
Original checksum: ce87d325f58abfee2a0ca73417aaf5bb
Well formed: true
Valid: true
Page count: 102
Activity of users you follow
User Activity Date