DocumentCode
2372885
Title
Multi-resolution Next Location Prediction for Distributed Virtual Environments
Author
Pribyl, Jaroslav ; Zemcik, Pavel
Author_Institution
Dept. of Comput. Graphics & Multimedia, BUT, Brno, Czech Republic
fYear
2010
fDate
11-13 Dec. 2010
Firstpage
247
Lastpage
254
Abstract
Computing performance of today´s graphics hardware grows fast as well as amount of rendered data. Modern graphics engines enable a possibility to use an arbitrary number of textures with arbitrary resolutions. On the other hand, high quality distributed 3D virtual environments can´t exploit the computation power due to the limited network bandwidth. The problem mainly appears just in case the designers of such environments use high resolution textures. To overcome this streaming bottleneck an efficient prefetching scheme should be proposed. Instead of blind greedy scheduling policy we propose a scheme which exploits movement history of users to realize a look-ahead policy which enables the clients to retrieve potentially rendered data in advance. The prediction itself is established by Markov chains due to their ability to fast learning in conjunction with 2-state predictor which increases ability of the scheduling system to adapt to new habits of particular users.
Keywords
Markov processes; distributed processing; learning (artificial intelligence); rendering (computer graphics); scheduling; storage management; virtual reality; 2-state predictor; Markov chain; computing performance; distributed 3D virtual environment; fast learning; graphics hardware; high resolution texture; limited network bandwidth; look-ahead policy; movement history; multiresolution next location prediction; prefetching; rendered data; scheduling system; Markov chain; chain code; distributed virtual environment; k-state predictor; next location prediction; scheduling; streaming;
fLanguage
English
Publisher
ieee
Conference_Titel
Embedded and Ubiquitous Computing (EUC), 2010 IEEE/IFIP 8th International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-9719-5
Electronic_ISBN
978-0-7695-4322-2
Type
conf
DOI
10.1109/EUC.2010.43
Filename
5703523
Link To Document