A Continuous Matching Algorithm for Interest Management in Distributed Virtual Environments

Elvis S. Liu, G. Theodoropoulos
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引用次数: 8

Abstract

Interest management provides scalable data distribution for large-scale distributed virtual environments by filtering irrelevant messages on the network. The interest matching process is essential for most of the interest management schemes which determines what data should be sent to the participants as well as what data should be filtered. Most of the existing interest matching approaches focus on reducing the computational overhead of the matching process. However, they have a fundamental disadvantage - they perform interest matching at discrete time intervals. As a result, they would fail to report events between two consecutive time-steps of simulation. If participants ignore these missing events, they would most likely perform incorrect simulations. This paper presents a new algorithm for continuous interest matching which aims to capture missing events between discrete time-steps. Although our approach requires additional matching steps, we employ a efficient algorithm to significantly reduce this overhead.
分布式虚拟环境下兴趣管理的连续匹配算法
兴趣管理通过过滤网络上无关的消息,为大规模分布式虚拟环境提供可伸缩的数据分发。兴趣匹配过程是大多数兴趣管理方案的关键,它决定了哪些数据应该发送给参与者以及哪些数据应该被过滤。现有的兴趣匹配方法大多侧重于减少匹配过程的计算开销。然而,它们有一个根本的缺点——它们在离散的时间间隔内执行兴趣匹配。因此,它们将无法报告两个连续模拟时间步之间的事件。如果参与者忽略这些缺失的事件,他们很可能会执行错误的模拟。本文提出了一种新的连续兴趣匹配算法,旨在捕获离散时间步之间的缺失事件。尽管我们的方法需要额外的匹配步骤,但我们采用了一种有效的算法来显著减少这种开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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