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Virtual Machines for Virtual Worlds.

Authors: Sanatinia, Amirali; Oliver, Iain Angus; Miller, Alan Henry David; Allison, Colin;

Virtual Machines for Virtual Worlds.

Abstract

Multi User Virtual Worlds provide a simulated immersive 3D environment that is similar to the real world. Popular examples include Second Life and OpenSim. The multi-user nature of these simulations means that there are significant computational demands on the processes that render the different avatar-centric views of the world for each participant, which change with every movement or interaction each participant makes. Maintaining quality of experience can be difficult when the density of avatars within the same area suddenly grows beyond a relatively small number. As such virtual worlds have a dynamic resource-on-demand need that could conceivably be met by Cloud technologies. In this paper we make a start to assessing the feasibility of using the Cloud for virtual worlds by measuring the performance of virtual worlds in virtual machines of the type used for Clouds. A suitable benchmark is researched and formulated and the construction of a test-bed for carrying out load experiments is described. The system is then used to evaluate the performance of virtual worlds running in virtual machines. The results are presented and analysed before presenting the design of a system that we have built for managing virtual worlds in the cloud.

Country
United Kingdom
Related Organizations
Keywords

QA75, QA75 Electronic computers. Computer science

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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