Efficient data structures for discovery in high level architecture (HLA)


The High Level Architecture (HLA) is a prototype architecture for constructing distributed simulations. HLA is a standard adopted by the Department of Defense (DOD) for development of simulation environments. An important goal of the HLA is to reduce the amount of data routing between simulations during run-time. The Runtime Infrastructure (RTI) is an operating system that is responsible for data routing between the simulations in HLA. The data routing service is provided by the Data Distribution Manager of the RTI. Several methods have been proposed and used for the implementation of data distribution services. The grid-based filtering method, the interval tree method, and the quad-tree method are examples. This thesis analyzes and compares two such methods: the grid and the quad-tree, in regards to their use in the discovery of intersections of publications and subscriptions. The number of false positives and the CPU time of each method are determined for typical cases. For most cases, the quad-tree methos produces less false positives. This method is best suited for large simulations where the cost of maintaining false positives, or non-relevant entities, may be prohibitive. For most cases, the grid method is faster than the quad-tree method. This method may be better suited for small simulations where the host has the capacity to accommodate false positives. The results of this thesis can be used to decide which of the two methods is better suited to a particular type of simulation exercise.


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Thesis Completion





Petrasko, Brian E.


Bachelor of Science (B.S.)


College of Engineering

Degree Program

Computer Engineering


Dissertations, Academic -- Engineering;Engineering -- Dissertations, Academic;







Access Status

Open Access

Length of Campus-only Access


Document Type

Honors in the Major Thesis

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