2 research outputs found
An Information-Based Dynamic Extrapolation Model for Networked Virtual Environments
Various Information Management techniques have been developed to help maintain a consistent shared virtual world in a
Networked Virtual Environment. However, such techniques have to be carefully adapted to the application state dynamics and
the underlying network. This work presents a novel framework that minimizes inconsistency by optimizing bandwidth usage to
deliver useful information. This framework measures the state evolution using an information model and dynamically switches
extrapolation models and the packet rate to make the most information-efficient usage of the available bandwidth. The results
shown demonstrate that this approach can help optimize consistency under constrained and time-varying network conditions
An Information-Theoretic Framework for Consistency Maintenance in Distributed Interactive Applications
Distributed Interactive Applications (DIAs) enable geographically dispersed users
to interact with each other in a virtual environment. A key factor to the success
of a DIA is the maintenance of a consistent view of the shared virtual world for
all the participants. However, maintaining consistent states in DIAs is difficult
under real networks. State changes communicated by messages over such networks
suffer latency leading to inconsistency across the application. Predictive Contract
Mechanisms (PCMs) combat this problem through reducing the number of messages
transmitted in return for perceptually tolerable inconsistency. This thesis examines
the operation of PCMs using concepts and methods derived from information theory.
This information theory perspective results in a novel information model of PCMs
that quantifies and analyzes the efficiency of such methods in communicating the
reduced state information, and a new adaptive multiple-model-based framework for
improving consistency in DIAs.
The first part of this thesis introduces information measurements of user behavior
in DIAs and formalizes the information model for PCM operation. In presenting the
information model, the statistical dependence in the entity state, which makes using
extrapolation models to predict future user behavior possible, is evaluated. The
efficiency of a PCM to exploit such predictability to reduce the amount of network
resources required to maintain consistency is also investigated. It is demonstrated
that from the information theory perspective, PCMs can be interpreted as a form
of information reduction and compression.
The second part of this thesis proposes an Information-Based Dynamic Extrapolation
Model for dynamically selecting between extrapolation algorithms based on
information evaluation and inferred network conditions. This model adapts PCM
configurations to both user behavior and network conditions, and makes the most
information-efficient use of the available network resources. In doing so, it improves
PCM performance and consistency in DIAs