2010 · 10 citations · 18 references
Cluster ComputingEngineeringStreaming AlgorithmInterest MatchingData Streaming ArchitectureInterest ManagementContinuous InterestContinuous Matching AlgorithmData ScienceData MiningComplex Event ProcessingVirtual RealityData IntegrationData ManagementKnowledge DiscoveryComputer EngineeringDistributed Virtual EnvironmentsIntelligent Virtual EnvironmentComputer ScienceData Stream ManagementCollaborative Virtual EnvironmentSpatio-temporal Stream ProcessingVirtual EnterpriseCloud ComputingBusinessVirtual SpaceDistributed ManagementBig Data
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.
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Jonathan D. Cohen, Ming C. Lin, Dinesh Manocha et al. · 1995 · 619 citations · Full text
Chris Greenhalgh, Steve Benford · ACM Transactions on Computer-Human Interaction · 1995 · 391 citations · Full text
Engineering, Virtual Reality, Design +14
Exploiting reality with multicast groups
M. Macedonia, Michael Zyda, David R. Pratt et al. · IEEE Computer Graphics and Applications · 1995 · 188 citations