Semantic Consistency Optimization in Heterogeneous Virtual Environments
Carlos Correa, Ivan Marsic, Xiaodong Sun · 2004
Collaborative virtual environments with heterogeneous computing resources and user preferences often reduce data fidelity to accommodate such heterogeneity. Given the resource limitations and user preferences, the problem is to optimize the fidelity degradation so as to achieve maximum semantic consistency across the different data representations. Consistency maximization can be formulated as an integer-programming problem, wherein constraints are resource limitations and user preferences. We consider several formulations of the problem, some of which do not enforce topological constraints in degraded representation, while others do. The solutions to this problem result in reduced amounts of distributed data which conserve network bandwidth and other system resources. Experimental results and proposed topics for further research are also presented.