Consensus Based Networking of Distributed Virtual Environments

Distributed Virtual Environments (DVEs) are challenging to create as the goals of consistency and responsiveness become contradictory under increasing latency. DVEs have been considered as both distributed transactional databases and force-reflection systems. Both are good approaches, but they do have drawbacks. Transactional systems do not support Level 3 (L3) collaboration: manipulating the same degree-of-freedom at the same time. Force-reflection requires a client-server architecture and stabilisation techniques. With Consensus Based Networking (CBN), we suggest DVEs be considered as a distributed data-fusion problem. Many simulations run in parallel and exchange their states, with remote states integrated with continous authority. Over time the exchanges average out local differences, performing a distribued-average of a consistent, shared state. CBN aims to build simulations that are highly responsive, but consistent enough for use cases such as the piano-movers problem. CBN's support for heterogeneous nodes can transparently couple different input methods, avoid the requirement of determinism, and provide more options for personal control over the shared experience. Our work is early, however we demonstrate many successes, including L3 collaboration in room-scale VR, 1000's of interacting objects, complex configurations such as stacking, and transparent coupling of haptic devices. These have been shown before, but each with a different technique; CBN supports them all within a single, unified system

Semantische Modellierung virtueller Umgebungen auf Basis einer modularen Simulationsarchitektur

Fröhlich C. Semantische Modellierung virtueller Umgebungen auf Basis einer modularen Simulationsarchitektur. Bielefeld: Universitätsbibliothek Bielefeld; 2014

Consensus Based Networking of Distributed Virtual Environments.

Distributed Virtual Environments (DVEs) are challenging to create as the goals of consistency and responsiveness become contradictory under increasing latency. DVEs have been considered as both distributed transactional databases and force-reflection systems. Both are good approaches, but they do have drawbacks. Transactional systems do not support Level 3 (L3) collaboration: manipulating the same degree-of-freedom at the same time. Force-reflection requires a client-server architecture and stabilisation techniques. With Consensus Based Networking (CBN), we suggest DVEs be considered as a distributed data-fusion problem. Many simulations run in parallel and exchange their states, with remote states integrated with continous authority. Over time the exchanges average out local differences, performing a distribued-average of a consistent, shared state. CBN aims to build simulations that are highly responsive, but consistent enough for use cases such as the piano-movers problem. CBN's support for heterogeneous nodes can transparently couple different input methods, avoid the requirement of determinism, and provide more options for personal control over the shared experience. Our work is early, however we demonstrate many successes, including L3 collaboration in room-scale VR, 1000's of interacting objects, complex configurations such as stacking, and transparent coupling of haptic devices. These have been shown before, but each with a different technique; CBN supports them all within a single, unified system

Scene Synchronization in Close Coupled World Representations using SCIVE

International audienceThis paper introduces SCIVE, a Simulation Core for Intelligent Virtual Environments. SCIVE provides a Knowledge Representation Layer (KRL) as a central organizing structure. Based on a semantic net, it ties together the data representations of the various simulation modules, e.g., for graphics, physics, audio, haptics or Artificial Intelligence (AI) representations. SCIVE's open architecture allows a seamless integration and modification of these modules. Their data synchronization is widely customizable to support extensibility and maintainability. Synchronization can be controlled through filters which in turn can be instantiated and parametrized by any of the modules, e.g., the AI component can be used to change an object's behavior to be controlled by the physics instead of the interaction- or a keyframe-module. This bidirectional inter- module access is mapped by, and routed through, the KRL which semantically reflects all objects or entities the simulation comprises. Hence, SCIVE allows extensive application design and customization from low-level core logic, module configuration and flow control, to the simulated scene, all on a high-level unified representation layer while it supports well known development paradigms commonly found in Virtual Reality application

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Knowledge Representation Layer (KRL)  as a central organizing structure. Based   on   a   semantic   net,   it   ties   together   the   data representations of   the   various   simulation   modules,   e.g.,   for graphics,  physics,  audio,  haptics or Artificial Intelligence (AI) representations. SCIVE's   open   architecture   allows   a   seamless integration and   modification   of   these   modules. Their   data synchronization is widely customizable to support extensibility and maintainability. Synchronization can be controlled through filters which in turn can be instantiated and parametrized by any of the modules,  e.g.,  the AI component can be used to change an object's behavior to be controlled by the physics instead of the interaction   or   a   keyframemodule. This   bidirectional   intermodule access is   mapped   by,   and   routed   through,   the   KRL which semantically reflects all objects or entities the simulation comprises. Hence,   SCIVE   allows   extensive   application   design and customization   from   lowlevel   core   logic,   module configuration and flow control,  to the simulated scene,  all on a highlevel unified   representation   layer   while   it   supports   well known development   paradigms   commonly   found   in   Virtual Reality applications