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Hull, Craig, Charles, D. K., Morrow, Philip and Parr, Gerard 
ORCID: https://orcid.org/0000-0002-9365-9132
(2015)
FRAGED: A framework for adaptive game execution and delivery to improve the quality of experience in network aware games.
In:
PGNET 2014: The 15th National Annual Postgraduate Symposium on the Convergence of Telecommunication.
Liverpool John Moores University, GBR.
Abstract
With the release of the next generation of game consoles and PC based game technologies as well as improvements to internet infrastructures there is an increased focus on distributed and cloud based game services. A key motivation for this change may be due to a desire among game developers and publishers to control and manage digital rights and to expand market potential through digital distribution and download content. However with this increased focus on server centric gaming the quality of experience for the users becomes a major issue. With the increasing variation in gaming hardware and limits on the network, the end user may not have the required bandwidth, network traffic may be too high or they may be too distant from the server which causes an increase in latency. Each of these can have an impact on a user's experience of gameplay. The ideal scenario would be for all game players to have an equal quality of experience in playing a game, irrespective of game hardware requirements, play location and variability of the quality of service across a network. In this paper we propose a framework for adaptive game execution and delivery (FRAGED) that can be used to design and implement a distributed game. FRAGED's emphasis is on cloud assistance rather than cloud streaming, where the quality of experience for game players can be maintained through the use of a system of distributed game asset streaming and code execution. We discuss the use of software agents as an integral aspect of the management process and present a criteria for agent monitoring and improving quality of experience.
| Item Type: | Book Section |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | Pure Connector |
| Date Deposited: | 15 Nov 2016 15:00 |
| Last Modified: | 10 Dec 2024 01:11 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/61354 |
| DOI: |
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