  Dead Reckoning mechanism allows reducing the network utilization considerably
when used in Distributed Interactive Simulation Applications. However, this
technique often ignores available contextual information that may be
influential to the state of an entity, sacrificing remote predictive accuracy
in favor of low computational complexity. The remainder of this paper focuses
on the analysis of the Dead Reckoning Algorithms. Some contributions are
expected and overviews of the major bandwidth reduction techniques currently
investigated are discussed. A novel extension of Dead Reckoning based on ANFIS
systems is suggested to increase the network availability and fulfilling the
required QoS in such applications. The model shows it primary benefits
regarding the other research contributions, especially in the decision making
of the behavior of simulated entities.
