Survey study of the QoS Management in Distributed Interactive Simulation Through Dead Reckoning Algorithms

TL;DR

This survey reviews Dead Reckoning algorithms in Distributed Interactive Simulation, analyzing their effectiveness in QoS management, and introduces an ANFIS-based extension to improve network availability and entity behavior prediction.

Contribution

It provides an overview of current bandwidth reduction techniques and proposes a novel ANFIS-based Dead Reckoning extension to enhance QoS in simulation applications.

Findings

ANFIS-based Dead Reckoning improves network availability

The model enhances decision-making for simulated entities

Bandwidth reduction techniques are critically analyzed

Abstract

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.