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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Author: search.filters.author.Baras, John S.Subject: search.filters.subject.Systems Integration Methodology

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    An Automated, Distributed, Intelligent Fault Management System for Communication Networks
    (1999) Li, Hongjun; Baras, John S.; Mykoniatis, George; ISR; CSHCN
    In this paper we present a Distributed Intelligent Fault Management (DIFM) system for communication networks. The overall architecture of the proposed system is based on a distributed, cooperative, multi-agent paradigm, with probabilistic networks as the framework for knowledge representation and evidence inferencing. We adopt the management by delegation paradigm for network monitoring and integrate both hard and soft faults.
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    An Architecture for Internet Service via Broadband Satellite Networks
    (1999) Bharadwaj, Vijay G.; Baras, John S.; Butts, Norman P.; Baras, John S.; ISR; CSHCN
    High bandwidth satellites hold out the promise of a rapidly deployablecommunications infrastructure with a natural support for mobility. However,the Transmission Control Protocol (TCP), widely used in the Internet, performspoorly over satellite links, and this presents an obstacle to thedeployment of such systems. We present an architecture that overcomesthese problems and provides an approach to building complex heterogeneousnetworks from simple units. We also present some results from our initialimplementation, which uses TCP connection splitting to improve TCPperformance over satellite links.
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    Disseminating Updates to Mobile Clients
    (1998) Stathatos, Konstantinos; Roussopoulos, Nick; Baras, John S.; ISR; CSHCN
    In this paper, we address the problem of propagating data updates to alarge number of mobile clients. Typically, mobile clients operateautonomously, i.e., disconnected from data servers, for prolongedperiods of time relying on locally replicated corporate data (e.g.,database views, file systems). From time to time, they need to refreshtheir replicas with data changes registered at a central datarepository. We propose a hybrid approach for delivering these updatesto the clients. We use a broadcast channel to "cache on the air"fresh updates for as long as they are high on demand. At the sametime, any requests for older updates are individually serviced by theserver through a separate channel. The air-caching satisfies the bulkof clients' needs, increasing data throughput many-fold compared totraditional data delivery mechanisms. We describe a hierarchicalair-cache structure, and analyze the performance of broadcasting a logof committed updates. Based on that, we propose a technique thatdynamically modifies the contents and the structure of the air-cacheaccording to the number and the (dis)connection habits of the clients.Through extensive simulations, we demonstrate the adaptiveness,efficiency, and practicality of the proposed system even for verylarge client populations.
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    Integrated, Distributed Fault Management for Communication Networks
    (1998) Baras, John S.; Li, Hongjun; Mykoniatis, G.; Baras, John S.; ISR; CSHCN
    This report describes an integrated, distributed fault management (IDFM) system for communication networks. The architecture is based on a distributed intelligent agent paradigm, with probabilistic networks as the framework for knowledge representation and evidence inferencing. A static strategy for generating the suggestive test sequence is proposed, based on which a heuristic dynamic strategy is initiated. Another dynamic strategy, formulated as a Markov decision problem, is also provided. To solve this problem, reinforcement learning techniques are investigated.
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    Extensions of DBS and Hybrid Internet
    (1997) Karir, Manish; Bharadwaj, Vijay G.; Holleman, Keith; Suphasindhu, Narin; Papademetriou, Spyro; Baras, John S.; ISR; CSHCN
    There has been a large amount of research dedicated to extending the asymmetric networks provided by receive-only Direct Broadcast Satellite systems like Hughes Network Systems' DirecPC product. One way to further develop Direct Broadcast Satellite services and to offset the high initial cost of these systems is to implement techniques that will allow one satellite receiver to act as a gateway for many clients to receive information. This would also help broaden the range of services provided by DBS systems. Besides providing direct-to-home traffic, DBS can be used to distribute bulk traffic to the local-loop distributors (direct-to-curb). We describe some experiments which extend the DBS system, in particular, the DirecPC and DirecTV DBS, by using the PC with the satellite receiver as a gateway to connect networks together. We also discuss simple methods of receiving multimedia traffic from the multicast backbone (MBONE) [Cas94] over the satellite link, and distributing it, through this gateway, to end users.

    The research and scientific content in this material will be presented at the 2nd ACM International Workshop on Satellite-Based Information Services (WOSBIS), October 1, 1997, Budapest, Hungary.
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    Integrated Product and Process Design Environment Tool for Manufacturing T/R Modules
    (1997) Karne, Ramesh K.; Lai, Hsing-Tsu; Dandekar, Swati V.; Baras, John S.; Ball, Michael O.; Bashyam, Sridhar; Trichur, Vinai S.; Karir, Manish; Kebede, Abraham; Williams, Jim; ISR; CSHCN
    We present a decision making assistant tool for integrated product and process design environment for manufacturing applications. Specifically, we target microwave modules which use Electro-mechanical components and require optimal solutions to reduce cost, improve quality, and gain leverage in time to market the product. This tool will assist the product and process designer to improve their productivity and also enable to cooperate and coordinate their designs through a common design interface. We consider a multiobjective optimization model that determines components and processes for a given conceptual designs for microwave modules. This model outputs a set of solutions that are Pareto optimal with respect to cost, quality, and other metrics. In addition, we identify system integration issues for manufacturing applications, and propose an architecture which will serve as a building block to our continuing research in virtual manufacturing applications.
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    Performance Analysis of PNNI Routing in ATM Networks: Hierarchical Reduced Load Approximation
    (1997) Xie, Hui; Baras, John S.; ISR; CSHCN
    In this paper, we investigate the performance issue of PNNI routing for ATM networks. A brief introduction to PNNI routing protocol is given. We extend the reduced load approximation algorithm to ATM networks with PNNI routing. A hierarchical reduced load approximation scheme is proposed. The scheme includes two steps: the reduced load approximation algorithm is first applied on the aggregated network at upper level; then the approximation is refined at the lower level as needed using the results from the upper level. This hierarchical scheme follows the PNNI routing framework and results a fast and scaleable algorithm.
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    Automated Network Fault Management
    (1997) Baras, John S.; Ball, Michael O.; Gupta, Sonjai K.; Viswanathan, P.; Shah, P.; ISR; CSHCN
    Future military communication networks will have a mixture of backbone terrestrial, satellite and wireless terrestrial networks. The speeds of these networks vary and they are very heterogeneous. As networks become faster, it is not enough to do reactive fault management. Our approach combines proactive and reactive fault management . Proactive fault management is implemented by dynamic and adaptive routing. Reactive fault management is implemented by a combination of a neural network and an expert system. The system has been developed for the X.25 protocol. Several fault scenarios were modeled and included in the study: reduced switch capacity, increased packet generation rate of a certain application, disabled switch in the X.25 cloud, disabled links. We also modeled occurrence of alarms including severity of the problem, location of the event and a threshold. To detect and identify faults we use both numerical data associated with the performance objects (attributes) in the MIB as well as SNMP traps (alarms). Simulation experiments have been performed in order to understand the convergence of the algorithms, the training of the neural networks involved and the G2/NeurOn-Line software environment and MIB design.
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    Tactical and Strategic Communication Network Simulation and Performance Analysis
    (1997) Baras, John S.; Corson, M. Scott; Doan, Khoa; Jang, Kap D.; Liu, Mingyan D.; Misra, Archan; Xie, H.; ISR; CSHCN
    We describe a framework for the efficient modeling and performance evaluation of large networks consisting of mixture of strategic and tactical components. The method emphasizes hierarchical, layered techniques that are fed parametric models at the lower level. In addition to the algorithmic structure, and some initial algorithms we describe an object oriented software architecture that is under development to support these algorithmic methods in a distributed environment.
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    Adaptive Data Broadcast in Hybrid Networks
    (1997) Stathatos, K.; Roussopoulos, N.; Baras, John S.; ISR; CSHCN
    Hybrid networks combine multiple communication modes and are fast, emerging as the most viable solution for the ever increasing demand for bandwidth and data services. Taking advantage of this new technology, we are proposing a hybrid scheme which effectively combines broadcast for massive data dissemination and unicast for individual data delivery. The goal is to build highly scalable systems with small response time. In this paper, we describe a technique that continuously adapts the broadcast content to match the hot-spot of the workload. We show that the hot-spot can be accurately obtained by, monitoring the ``broadcast misses'' observed through direct requests.

    This is a major departure from all other broadcast optimization schemes which are handicapped by their total reliance on complete knowledge of both ``hits'' and ``misses''. We also show that the proposed adaptive scheme performs effectively even under very dynamic and rapidly changing workloads. Extensive simulation results demonstrate both the scalability and versatility of, the technique. Another basic result obtained in this paper is that the overall, system's throughput depends only on the size of the hot-spot and not on the volume of the workload. This has far reaching implications for very large scale and high volume wide area information systems.