Conducting business in network centric collaborative environments

The Destiny-class CyberCANOE (Destiny) is a Hybrid Reality environment that provides 20/20 visual acuity in a 13-foot-wide, 320-degree cylindrical structure comprised of tiled passive stereo-capable organic light emitting diode (OLED) displays. Hybrid Reality systems combine surround-screen virtual reality environments with ultra-high-resolution digital project-rooms. They are intended as collaborative environments that enable multiple users to work minimally encumbered for long periods of time in rooms surrounded by data in the form of visualizations that benefit from being displayed at resolutions matching visual acuity and/or in stereoscopic 3D. Destiny is unique in that it is the first Hybrid Reality system to use OLED displays and it uses a real-time GPU-based approach for minimizing stereoscopic crosstalk. This paper chronicles the non-trivial engineering research and attention-to-detail that is required to develop a production quality hybrid-reality environment by providing details about Destiny’s design and construction process. This detailed account of how a Hybrid Reality system is designed and constructed from the ground up will help VR researchers and developers understand the engineering complexity of developing such systems. This paper also discusses a GPU-based crosstalk mitigation technique and evaluation, and the use of Microsoft’s augmented reality headset, the HoloLens, as a design and training aid during construction.

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Situational awareness support to enhance teamwork in collaborative environments

Proceedings of the 15th European conference on Cognitive ergonomics the ergonomics of cool interaction - ECCE '08 ◽

10.1145/1473018.1473025 ◽

2008 ◽

Cited By ~ 5

Author(s):

Olga Kulyk ◽

Gerrit van der Veer ◽

Betsy van Dijk

Keyword(s):

Situational Awareness ◽

Collaborative Environments ◽

Awareness Support

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Toward a Faster Fault Tolerant Consensus to Maintain Data Consistency in Collaborative Environments

International Journal of Cooperative Information Systems ◽

10.1142/s0218843017500022 ◽

2017 ◽

Vol 26 (03) ◽

pp. 1750002

Author(s):

Fouad Hanna ◽

Lionel Droz-Bartholet ◽

Jean-Christophe Lapayre

Keyword(s):

Network Model ◽

Fault Tolerant ◽

Data Consistency ◽

Consensus Algorithm ◽

Simulation Platform ◽

Consensus Problem ◽

Collaborative Environments ◽

Consensus Algorithms ◽

Shared Data ◽

Simultaneous Process

The consensus problem has become a key issue in the field of collaborative telemedicine systems because of the need to guarantee the consistency of shared data. In this paper, we focus on the performance of consensus algorithms. First, we studied, in the literature, the most well-known algorithms in the domain. Experiments on these algorithms allowed us to propose a new algorithm that enhances the performance of consensus in different situations. During 2014, we presented our very first initial thoughts to enhance the performance of the consensus algorithms, but the proposed solution gave very moderate results. The goal of this paper is to present a new enhanced consensus algorithm, named Fouad, Lionel and J.-Christophe (FLC). This new algorithm was built on the architecture of the Mostefaoui-Raynal (MR) consensus algorithm and integrates new features and some known techniques in order to enhance the performance of consensus in situations where process crashes are present in the system. The results from our experiments running on the simulation platform Neko show that the FLC algorithm gives the best performance when using a multicast network model on different scenarios: in the first scenario, where there are no process crashes nor wrong suspicion, and even in the second one, where multiple simultaneous process crashes take place in the system.

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