59 research outputs found
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Integrated Analysis of Environment-driven Operational Effects in Sensor Networks
There is a rapidly growing need to evaluate sensor network functionality and performance in the context of the larger environment of infrastructure and applications in which the sensor network is organically embedded. This need, which is motivated by complex applications related to national security operations, leads to a paradigm fundamentally different from that of traditional data networks. In the sensor networks of interest to us, the network dynamics depend strongly on sensor activity, which in turn is triggered by events in the environment. Because the behavior of sensor networks is sensitive to these driving phenomena, the integrity of the sensed observations, measurements and resource usage by the network can widely vary. It is therefore imperative to accurately capture the environmental phenomena, and drive the simulation of the sensor network operation by accounting fully for the environment effects. In this paper, we illustrate the strong, intimate coupling between the sensor network operation and the driving phenomena in their applications with an example sensor network designed to detect and track gaseous plumes
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On the Reversibility of Newton-Raphson Root-Finding Method
Reversibility of a computational method is the ability to execute the method forward as well as backward. Reversible computational methods are generally useful in undoing incorrect computation in a speculative execution setting designed for efficient parallel processing. Here, reversibility is explored of a common component in scientific codes, namely, the Newton-Raphson root-finding method. A reverse method is proposed that is aimed at retracing the sequence of points that are visited by the forward method during forward iterations. When given the root, along with the number of iterations, of the forward method, this reverse method is aimed at backtracking along the reverse sequence of points to finally recover the original starting point of the forward method. The operation of this reverse method is illustrated on a few example functions, serving to highlight the method's strengths and shortcomings
Scalable RTI-Based Parallel Simulation of Networks
©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.Presented at the Seventeenth Workshop on Parallel and Distributed Simulation (PADS 03), 2003Federated simulation interfaces such as the High Level
Architecture (HLA) were designed for interoperability,
and as such are not traditionally associated with high performance
computing. In this paper, we present results
of a case study examining the use of federated simulations
using runtime infrastructure (RTI) software to realize
large-scale parallel network simulators. We examine the
performance of two different federated network
simulators, and describe RTI performance optimizations
that were used to achieve efficient execution. We show
that RTI-based parallel simulations can scale extremely
well and achieve very high speedup. Our experiments
yielded more than 80-fold scaled speedup in simulating
large TCP/IP networks, demonstrating performance of up
to 6 million simulated packet transmissions per second on
a Linux cluster. Networks containing up to two million
network nodes (routers and end systems) were simulated
Coping at the User-Level with Resource Limitations in the Cray Message Passing Toolkit MPI at Scale: How Not to Spend Your Summer Vacation
ABSTRACT: As the number of processor cores available in Cray XT series computers has rapidly grown, users have increasingly encountered instances where an MPI code that has previously worked for years unexpectedly fails at high core counts ("at scale") due to resource limitations being exceeded within the MPI implementation. Here, we examine several examples drawn from user experiences and discuss strategies for working around these difficulties at the user level
Techniques for efficient parallel simulation and their application to large-scale telecommunication network models
Ph.D.Richard M. Fujimot
Generating Perfect Reversals of Simple Linear-Codes
Bi-directional execution - executing forward as well as in reverse - is useful in many contexts. However, traditional techniques for bi-directional execution are not scalable, as they require infinite storage in the presence of "destructive" assignments. We present a new approach that eliminates the scalability problem for bi-directional execution of a class of functions called linear codes, which are sequences of assignments of arbitrary linear expressions to variables. Examples of linear codes include Fibonacci-like sequence generators, and operators such as shift, swap and rotate. We present an algorithm to generate perfect forward-reverse code pair from any given linear code, and show that any linear code can be perfectly inverted despite the presence of destructive assignments and apparent singularities in the input code. While existing techniques require memory size proportional to forward execution length, the code generated by our algorithm uses bounded amount of memory. The memory is proportional only to the number of variables in the given forward code, and is independent of both forward code size and forward execution length
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