Conference Paper

Maximising Concurrency and Scalability in a Consistent, Causal, Distributed Virtual Reality System Whilst Minimising the Effect of Network Delays.

Dept. of Cybern., Reading Univ.
DOI: 10.1109/ENABL.1997.630808 In proceeding of: 6th Workshop on Enabling Technologies (WET-ICE '97), Infrastructure for Collaborative Enterprises, 18-20 June 1997, MIT, Cambridge, MA, USA, Proceedings
Source: DBLP

ABSTRACT The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delays.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In distributed virtual environments, hosts typically have to react to events within a time span which is less than the network latency. As a consequence, hosts do routinely take actions although the system is in an inconsistent state. This has a noticeable influence on the perceived quality of these actions and their effect on the application. We argue that the level of this influence depends on the degree of inconsistency. In this paper, we tackle two fundamental questions: How does the degree of inconsistency influence the perceived quality of the users' actions? How can the degree of inconsistency be quantified? We propose a benchmark test for comparing different consistency algorithms with each other which consists of two measures of inconsistency and a sample scenario. For two different consistency algorithms, we compare the results of our benchmark test with the results of a user evaluation test and a simple yield measure.
    Parallel and Distributed Systems, 2008. ICPADS '08. 14th IEEE International Conference on; 01/2009
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In distributed virtual environments (DVEs) the data on which the hosts operate is not consistent at all times. To restore data consistency, the DVE has to employ a consistency algorithm. Unfortunately, all existing DVEs have been built for specific application scenarios, which makes it impossible to compare the consistency algorithms and to choose a suitable candidate for a new scenario. To overcome this, we have created a modular simulator-based DVE testbed named Adam with the ability to plug in different application scenarios as well as different consistency algorithms and network constraints. The testbed also contains a large set of measurement tools. Our testbed currently supports two application scenarios and several of the most common consistency algorithms found in the literature. We can compare the solutions on an objective scale and confirm that optimistic consistency typically outperforms loose consistency.
    Distributed Computing Systems Workshops, 2008. ICDCS '08. 28th International Conference on; 07/2008
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A distributed virtual environment (DVE) is a software system that allows users on a network to interact with each other by sharing a common view of their states. As users are geographically distributed over large networks like the Internet and the number of users increases, scalability is a key aspect to consider for real-time interaction. Various solutions have been proposed to improve the scalability in DVE systems but they are either focused on only specific aspects or customized to a target application. In this paper, we classify the approaches for improving scalability of DVE into four categories: communication architecture, interest management, concurrency control, and data replication. We then propose a scalable network framework for DVEs, ATLAS. Incorporated with our various scalable schemes, ATLAS meets the scalability of a system as a whole. By providing system developers with a set of APIs as a network infrastructure, ATLAS intends to support various applications The integration experiences of ATLAS with several virtual reality systems ensures the versatility of the proposed solution.
    Presence Teleoperators &amp Virtual Environments 01/2007; 16:125-156. · 1.04 Impact Factor

Full-text (6 Sources)

Available from
Jun 4, 2014