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Item

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Performance Analysis of Layer Partition-based Matching Algorithm in Data Distribution Management

http://hdl.handle.net/20.500.12678/0000006340
f0cbec63-6a26-4443-a653-0210b32067eb
787df742-f465-4855-b978-9643bfff770a
None
Name / File License Actions
Performance Performance Analysis of Layer Partition-based Matching Algorithm in Data Distribution Management.pdf (1.6 Mb)
© 2018 ICAIT
Publication type
Conference paper
Upload type
Publication
Title
Title Performance Analysis of Layer Partition-based Matching Algorithm in Data Distribution Management
Language en
Publication date 2018-11-02
Authors
Nwe Nwe Myint Thein
Description
High Level Architecture (HLA) is architecture for reuse and interoperation of simulations. In HLA paradigm, the Runtime Infrastructure (RTI) provides a set of services. Data Distribution Management (DDM) service reduces message traffic over the network. The evolution of the DDM service in HLA provides solutions to problems by using filtering mechanism that is suitable for large-scale simulation. These services rely on the computation of the intersection between “update” and “subscription” regions. When calculating the intersection between update regions and subscription regions, the higher computation overhead can occur. Currently, there are several main DDM filtering algorithms. The paper analyzes the performance of layer partition-based algorithms (LPM) for the matching process based on the different overlapping rate. The LPM algorithm provides the more definite matching area between update region and subscription region. The LPM algorithm guarantees low computational overheads for matching process of higher overlapping rate between the regions and reduce the irrelevant message among federates.
Keywords
HLA, DDM, Layer Partition-based, Matching Algorithm, Modeling and Simulation, Distributed System
Conference papers
ICAIT-2018
1-2 November, 2018
2nd International Conference on Advanced Information Technologies
Yangon, Myanmar
Simulation and Modeling in Software Approach
https://www.uit.edu.mm/icait-2018/
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