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The memory resources required by network simulations can grow quadratically with size of the simulated network. In simulations that use routing tables at each node to perform perhop packet forwarding, the storage required for the routing tables is O(N 2 ), where N is the number of simulated network nodes in the topology. Additionally, the CPU time required in the simulation environment to compute and populate these routing tables can be excessive and can dominate the overall simulation time. We propose new routing technique, known as Neighbor-Index Vectors, or NIx-Vectors, which eliminates both the storage required for the routing tables and the CPU time required to compute them. We show experimental results using NIx-Vector routing in the popular network simulator ns. With our technique, we achieve a near order of magnitude increase in the maximum size of a simulated network running ns on a single workstation. Further, we demonstate an increase of two orders of magnitu...

This paper presents the issues involved in the design and development of ussf. Parallel simulation techniques are used to enable optimal time versus resource tradeos in ussf. The techniques employed in the framework to reduce and regulate the memory requirements of the simulations are described. The API needed for model development is illustrated. The results obtained from the experiments conducted using various system models with two parallel simulation kernels (comparing a conventional approach with ussf) are also presented. Key Words: Large Scale Modeling, Parallel and Distributed Simulation, Time Warp Simulation, Unsynchronized Simulation 1 Support for this work was provided in part by the Defense Advanced Research Projects Agency under contract DABT63-96{C{0055. 1 2 RAO AND WILSEY 1. INTRODUCTION Modern systems such as microprocessors and communicat

Current simulation technologies support at most hundreds of thousands of nodes, and fall short on the emerging large-scale networking systems that usually involve millions of nodes. We meet this challenge with our distributed simulation engine that is able to run millions of instances and is tested with a production P2P protocol, using commodity PC clusters. This simulation engine is part of the WiDS toolkit, which takes a holistic approach to the research and development of distributed systems. We also propose a critical optimization, called Slow Message Relaxation (SMR), to trade simulation accuracy for performance. By taking advantage of the fact that distributed protocols are resilient to network fluctuation, SMR executes events in a logical time window much wider than the conventional lookahead scheme allows. We analyze and bound the potential effect of the distortion on application logic and other general metrics. Our experiments demonstrate that the simulation engine is able to achieve order of a magnitude speedup with statistically accurate simulation results. 1.

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Active networking techniques embed computational capabilities into conventional networks thereby massively increasing the complexity and customization of the computations that are performed with a network. In depth studies of these large and complex networks that are still in their nascent stages cannot be effectively performed using analytical methods. Hence, discrete event simulation techniques are the only viable means to study and analyze active networking architectures. Furthermore, customized and flexible tools are required to for the analysis of active networks using simulation. This paper describes an integrated environment for the modeling and parallel simulation of active networks called Active Networks Simulation Environment (or ANSE). ANSE utilizes the Time Warp synchronized kernel of WARPED (a general purpose discrete event simulation kernel) to enable parallel simulation of active network models. ANSE also includes complete support for the modeling and simulation of active networks based on PLAN (Packet Language for Active Networks). This paper presents the issues involved in the design and development of ANSE. The Application Programming Interface (API) of ANSE is presented along with the issues involved in utilizing it to develop support for PLAN based active networks. The paper also presents some results obtained from the several experiments conducted to evaluate the effectiveness of ANSE. Our studies indicate that ANSE provides an effective environment for modeling and simulation of large scale active networks.

Discrete event simulations are widely used to study and analyze active and conventional networking architectures and protocols. Active networks must coexist and communicate with conventional networks to eectively utilize and extend the infrastructure of the Internet. Hence, large scale network simulations containing both conventional and active components should be conducted to study crucial scalability and performance issues. In this paper, a framework to enable parallel co-simulation of conventional and active networks is described. The framework integrates anse, a parallel Active Networks Simulation Environment, with NS , a popular sequential network simulator. Object oriented techniques that completely insulate the application modules from the modications have been employed for parallelizing NS in order to eliminate changes to the network models. This paper presents the design and implementation of the parallel co-simulation framework along with the results obtained from our cosi...

With the advent of standardization efforts such as the High Level Architecture (HLA) and Distributed Interactive Simulation (DIS), inter-operability of military simulation models has emerged as the chief design requirement. By enforcing strict conformance to the DIS and/or HLA, the Defense Modeling and Simulation Office (DMSO) has so far been able to "mix-and-match" different simulation models and frameworks to satisfy the military's simulation needs. However, by linking different legacy simulations (simulations previously designed to operate independently) together, the simulation now has to correctly handle multiple levels of detail in the interacting simulation entities. In addition, a given entity itself can be represented in different ways each with a different level of detail (also referred to as resolution or fidelity). A natural question to ask in this situation is why does the model require different resolutions? Why isn't one level of resolution sufficient to address all the ...

Recent breakthroughs in communication and software engineering has resulted in significant growth of web-based computing. Web-based techniques have been employed for modeling, simulation, and analysis of systems. The models for simulation are usually developed using component based techniques. In a component based model, a system is represented as a set of interconnected components. A component is a well defined software module that is viewed as a "black box" i.e., only its interface is of concern and not its implementation. However, the behavior of a component, which is necessary for simulation, could be implemented by different modelers including third party manufacturers. Web-based simulation environments enable effective sharing and reuse of components thereby minimizing model development overheads. In component based simulations, one or more components can be substituted during simulation with a functionally equivalent set of components. Such Dynamic Component Substitutions (DCS) provide an effective technique for selectively changing the level of abstraction of a model during simulation. It provides a tradeoff between simulation overheads and model details. It can be used to effectively study large systems and accelerate rare event simulations to desired scenarios of interest. DCS may also be used to achieve fault-tolerance in Web-based simulations. This paper presents the ongoing research to design and implement support for DCS in A Web-based Environment for Systems Engineering (WESE).

The model used in this report focuses on the analysis of ship waiting statistics and stock fluctuations under different arrival processes. However, the basic outline is the same: central to both models are a jetty and accompanying tankfarm facilities belonging to a new chemical plant in the Port of Rotterdam. Both the supply of raw materials and the export of finished products occur through ships loading and unloading at the jetty. Since disruptions in the plants production process are very expensive, buffer stock is needed to allow for variations in ship arrivals and overseas exports through large ships. Ports provide jetty facilities for ships to load and unload their cargo. Since ship delays are costly, terminal operators attempt to minimize their number and duration. Here, simulation has proved to be a very suitable tool. However, in port simulation models, the impact of the arrival process of ships on the model outcomes tends to be underestimated. This article considers three arrival processes: stock-controlled, equidistant per ship type, and Poisson. We assess how their deployment in a port simulation model, based on data from a real case study, affects the efficiency of the loading and unloading process. Poisson, which is the chosen arrival process in many client-oriented simulations, actually performs worst in terms of both ship delays and required storage capacity. Stock-controlled arrivals perform best with regard to ship delays and required storage capacity. In the case study two types of arrival processes were considered. The first type are the so-called stock-controlled arrivals, i.e., ship arrivals are scheduled in such a way, that a base stock level is maintained in the tanks. Given a base stock level of a raw material or ...