Formalizing a framework for dynamic hybrid strategy models in distributed interactive applications

Abstract

Predictive contract mechanisms such as dead reckoning are widely employed to support scalable remote entity modelling in Distributed Interactive Applications (DIAs). By employing a form of controlled inconsistency, a reduction in network traffic is achieved. Previously, we have proposed the Dynamic Hybrid Strategy Model (DHSM) as an extension to the concept of dead reckoning that adaptively selects extrapolation models based on the use of local performance criteria. In this paper, we formalize the notion of the DHSM as a generalized framework for network traffic reduction in DIAs, alongside a set of consistency metrics for use as local performance criteria.Keywords -distributed interactive applications, predictive contract mechanisms, dead reckoning, consistency, scalability. __________________________________________________________________________________________ I INTRODUCTIONA Distributed Interactive Application (DIA) is a distributed virtual reality system through which individuals can share information via individual and collaborative interaction with each other and their environment [1]. Distributed Interactive Applications offer the realization of simulated virtual worlds that embody a modern extension of communication, encompassing the concepts of shared time, shared space and shared presence [2]. The definition of a DIA encompasses a diverse range of applications that have seen rapid advances in technology and global popularity due to the widespread availability and ease-of-use of the Internet [3].The two primary factors limiting the large-scale deployment of a DIA are network latency and network bandwidth. Network latency refers to the delay in communication between two end-points, while network bandwidth refers to the rate at which data can be communicated per unit time between two end-points. High network latency and low network bandwidth capacity represent the largest contributors to the difficulties faced by DIAs in maintaining and supporting: (a) shared state consistency, (b) potential scalability, and (c) real-time interactivity.In this paper, we are concerned with the use of predictive contract mechanisms for the reduction of network traffic in DIAs, including the well-known dead reckoning algorithms formally defined in the IEEE Standard for Distributed Interactive Simulation (DIS) [4]. Traditional dead reckoning mechanisms often ignore available contextual information that may be influential to the state of an entity, sacrificing remote predictive accuracy in favour of low resource and computational overhead [2]. Previously, we have proposed an extension of dead reckoning, known as the Dynamic Hybrid Strategy Model (DHSM), that builds upon the foundation of the Hybrid Strategy Model (HSM) technique [5,6]. Both the HSM and the DHSM are hybrid predictive contract techniques that dynamically select remote extrapolation models based on local evaluation of current entity dynamics.In this paper, we formalize the concept of the DHSM as a generalized framework for the reduction of network traffic in D...

Improved Queuing Mechanism for Hybrid Load balancing Scheme in Interactive Application

“…Most of these focus on reducing the amount of data that must be transmitted to maintain consistency between users of the DIA. The most widely used algorithm for achieving this is dead reckoning, which predicts the future positions of users over a short term interval [14]. Dead reckoning reduces the number of packets that must be transmitted to maintain state consistency in the following way.…”

A Consistency Regulation Algorithm for Client-Server-based Multiplayer Computer Games

“…Thus, high consistency can be maintained, but at the cost of the responsitivity of the application, as all user input must first be approved by the server before being acted on, introducing delays between the time a player initiates an action and the time it takes place. Several different entity state consistency management methods exists for reducing network traffic while maintaining some level of consistency [5,8]. However, these methods are static in nature and do not adapt to changing network conditions, such as increases in latency or reduction in available bandwidth.…”