Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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    Advanced Orbiting Systems Data Generator/Simulator: A Functional Description of the Software (Version 3)
    (1994) Baras, John S.; Atallah, George C.; Fuja, Tom E.; Murad, A.; Jang, Kap D.; ISR; CSHCN
    The Advanced Orbiting System (AOS) Data Generator/Simulator is a software implementation of the transmitter (data generation) section of the CCSDS Recommendation 701.0-B-2 for Advanced Orbiting Systems: Networks and Data Links. An object-oriented approach to the simulation of a complex, high-performance communication protocol, it makes full use of the concepts of data-encapsulation and inheritance to ease implementation. The backbone of the software is a general-purpose packet description and generation module that may be used as part of any packet- based simulation software. The user-interface to the program is in the form of a command-language, designed to ease the process of generation of large, multiple data-streams. The output of the program may be configured for interpretation by a graphical user interface (for visual inspection of the data), or as a bit-stream suitable for further processing. This paper consists of three sections. The first two sections provide a brief, yet comprehensive description of the above CCSDS Recommendation. The various kinds and qualities of user-services, data units involved, and data-paths defined by the protocol are discussed. The different qualities of service (in terms or data reliability) available to the user (and the error-control schemes used to provide them) are also discussed. The last section describes the structure and user-interfaces of the AOS Data Generator/Simulator.
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    Hilbert R-Tree: An Improved R-Tree Using Fractals
    (1993) Kamel, Ibrahim; Faloutsos, Christos; ISR
    We propose a new R-tree structure that outperforms all the older ones. The heart of the idea is to impose a linear ordering on the data rectangles. This ordering has to be 'good', in the sense that it should cluster 'similar' data rectangles together, to minimize the area and perimeter of the resulting minimum bounding rectangles (MBRs). Among the orderings we tried, the '2D-c' method, the one that uses the (2d) hilbert value of the center of the rectangles, gives the best results.

    For a static database, the proposed ordering achieves superior packing, outperforming older packing methods [25], and the best dynamic method (R*-trees [3]). The savings are as high as 36% on real data.

    more importantly, we introduce a dynamic variation, the Hilbert R- tree: : Given the ordering, every node has a well- defined set of sibling nodes; thus, we can deploy the deferred splitting algorithms of the B* -trees. By adjusting the split policy, the Hilbert R-tree can achieve as high utilization as desired. We show that a '3-to-4' split policy achieves good results, consistently outperforming the R* -trees, with up to 28% savings on real data.

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    Linking Symbolic and Subsymbolic Computing
    (1993) Wilson, A.; Hendler, James A.; ISR
    The growing interest in integrating symbolic and subsymbolic computing techniques is manifested by the increasing number of hybrid systems that employ both methods of processing. This paper presents an analysis of some of these systems with respect to their symbolic/subsymbolic interactions. Then, a general purpose mechanism for linking symbolic and sub symbolic computing is introduced. Through the use of programming abstractions, an intermediary agent called a supervisor is created and bound to each subsymbolic network. The role of a supervisor is to monitor and control the network behavior and interpret its output. Details of the subsymbolic computation are hidden behind a higher level interface, enabling symbolic and subsymbolic components to interact at corresponding conceptual levels. Module level parallelism is achieved because subsymbolic modules execute independently. Methods for construction of hierarchical systems of subsymbolic modules are also provided.