227 research outputs found

    The Distributed Independent-Platform Event-Driven Simulation Engine Library (DIESEL)

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    The Distributed, Independent-Platform, Event-Driven Simulation Engine Library (DIESEL) is a simulation executive, capable of supporting both sequential and distributed discrete-event simulations. A system level specification is provided along with the expected behavior of each component within DIESEL. This behavioral specification of each component, along with the interconnection and interaction between the different components, provides a complete description of the DIESEL behavioral model. The model provides a considerable amount of freedom for an application developer to partition the simulation model, when building sequential and distributed applications with respect to balancing the number of events generated across different components. It also allows a developer to modify underlying algorithms in the simulation executive, while causing no changes to the overall system behavior so long as the algorithms meet the behavioral specifications. The behavioral model is object-oriented and developed using a hierarchical approach. The model is not targeted towards any programming language or hardware platform for implementation. The behavioral specification provides no specifics about how the model should be implemented. A complete and stable implementation of the behavioral model is provided as a proof-of-concept, and can be used to develop commercial applications. New and independent implementations of the complete model can be developed to support specific commercial and research efforts. Specific components of the model can also be implemented by students in an educational environment, using strategies different from the ones used within the current implementation. DIESEL provides a research environment for studying different aspects of Parallel Discrete-Event Simulation, such as event management strategies, synchronization algorithms, communication mechanisms, and simulation state capture capabilities

    The treatment of time in distributed simulation

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    Simulation is one of the most important tools to analyse, design, and operate complex processes and systems. Simulation allows us to make a 'trial and error' in order to understand a system and describe a problem. Therefore, it is of great interest to use simulation easily and practically. The advent of parallel processors and languages help simulation studies. A recent simulation trend is distributed simulation which may be called discrete- event simulation, because distributed simulation has a great potential for the speed-up. This thesis will survey discrete-event simulation and examine one particular algorithm. It will first survey simulation in general and secondly, distributed simulation. Distributed simulation has broadly two mechanisms: conservative and optimistic. The treatment of time in these mechanisms is different, we will look into both mechanisms. Finally, we will examine the conservative mechanism on a network of transputers using Occam. We will conclude with the result of the experiments and the perspective of distributed simulation

    Synchronous Parallel Emulation and Discrete Event Simulation System with Self-Contained Simulation Objects and Active Event Objects

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    The present invention is embodied in a method of performing object-oriented simulation and a system having inter-connected processor nodes operating in parallel to simulate mutual interactions of a set of discrete simulation objects distributed among the nodes as a sequence of discrete events changing state variables of respective simulation objects so as to generate new event-defining messages addressed to respective ones of the nodes. The object-oriented simulation is performed at each one of the nodes by assigning passive self-contained simulation objects to each one of the nodes, responding to messages received at one node by generating corresponding active event objects having user-defined inherent capabilities and individual time stamps and corresponding to respective events affecting one of the passive self-contained simulation objects of the one node, restricting the respective passive self-contained simulation objects to only providing and receiving information from die respective active event objects, requesting information and changing variables within a passive self-contained simulation object by the active event object, and producing corresponding messages specifying events resulting therefrom by the active event objects

    Improving Large-Scale Network Traffic Simulation with Multi-Resolution Models

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    Simulating a large-scale network like the Internet is a challenging undertaking because of the sheer volume of its traffic. Packet-oriented representation provides high-fidelity details but is computationally expensive; fluid-oriented representation offers high simulation efficiency at the price of losing packet-level details. Multi-resolution modeling techniques exploit the advantages of both representations by integrating them in the same simulation framework. This dissertation presents solutions to the problems regarding the efficiency, accuracy, and scalability of the traffic simulation models in this framework. The ``ripple effect\u27\u27 is a well-known problem inherent in event-driven fluid-oriented traffic simulation, causing explosion of fluid rate changes. Integrating multi-resolution traffic representations requires estimating arrival rates of packet-oriented traffic, calculating the queueing delay upon a packet arrival, and computing packet loss rate under buffer overflow. Real time simulation of a large or ultra-large network demands efficient background traffic simulation. The dissertation includes a rate smoothing technique that provably mitigates the ``ripple effect\u27\u27, an accurate and efficient approach that integrates traffic models at multiple abstraction levels, a sequential algorithm that achieves real time simulation of the coarse-grained traffic in a network with 3 tier-1 ISP (Internet Service Provider) backbones using an ordinary PC, and a highly scalable parallel algorithm that simulates network traffic at coarse time scales

    Concurrent cell rate simulation of ATM telecommunications network.

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    Experiments in distributed memory time warp

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