Paper
19 May 2005 A heuristic for efficient data distribution management in distributed simulation
Pankaj Gupta, Ratan K. Guha
Author Affiliations +
Abstract
In this paper, we propose an algorithm for reducing the complexity of region matching and efficient multicasting in data distribution management component of High Level Architecture (HLA) Run Time Infrastructure (RTI). The current data distribution management (DDM) techniques rely on computing the intersection between the subscription and update regions. When a subscription region and an update region of different federates overlap, RTI establishes communication between the publisher and the subscriber. It subsequently routes the updates from the publisher to the subscriber. The proposed algorithm computes the update/subscription regions matching for dynamic allocation of multicast group. It provides new multicast routines that exploit the connectivity of federation by communicating updates regarding interactions and routes information only to those federates that require them. The region-matching problem in DDM reduces to clique-covering problem using the connections graph abstraction where the federations represent the vertices and the update/subscribe relations represent the edges. We develop an abstract model based on connection graph for data distribution management. Using this abstract model, we propose a heuristic for solving the region-matching problem of DDM. We also provide complexity analysis of the proposed heuristics.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pankaj Gupta and Ratan K. Guha "A heuristic for efficient data distribution management in distributed simulation", Proc. SPIE 5805, Enabling Technologies for Simulation Science IX, (19 May 2005); https://doi.org/10.1117/12.604070
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Cited by 1 scholarly publication.
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KEYWORDS
Computer simulations

Data modeling

Standards development

Algorithm development

Computing systems

Receivers

Remote sensing

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