Applying Distributed Simulation

2011

Computing technology has advanced dramatically over the last twenty years, enabling new applications for networked simulation. Along with these applications are architectures and standards that support the interoperability of heterogeneous simulations. This paper begins by looking at the historical roots of distributed simulation, from an architecture and policy perspective. The paper then examines distributed simulation as a technology, which is based on the science of distributed systems. The paper identifies two key characteristics of distributed systems and then describes the modern distributed simulation architectures based on these characteristics.

Over the past few years there has been rapid growth in the demand for mobile communications that has led to intensive research and development of complex PCS (personal communication service) networks. Capacity planning and performance modeling are necessary to maintain a high quality of service to the PCS subscriber while minimizing costs. The analysis of these complex networks requires exible, yet time eecient modeling tools. To this end, we demonstrate that distributed simulation is one such modeling tool. In this study, we develop a model for PCS simulations that is suitable for execution on distributed computing platforms. This model is then validated using pre-viously derived analytical results. We show that this validated distributed simulation using 8 work-stations can reduce execution time from 20 hours to 3.5 hours. Next, as an example of distributed simulation's exibility, the model is extended to allow for diierent call hold time distributions and simultaneous call ar...

Proceedings of the 38th …, 2006

Distributed simulation is used very little in industry, especially when compared with the interest in distributed simulation from research and from the military domain. In order to answer the question why industry lags behind, the authors have carried out an extensive survey, using a questionnaire and interviews, with users, vendors, and developers of distributed simulation products, as well as with vendors of non-distributed simulation software. This paper reports on the second part of the survey, namely a series of open ended interviews. We report on the responses we obtained indicating the discrepancies between the different "worlds". A categorization of these responses is given using which it is possible to formulate clear guidelines for further developments of standards for distributed simulation.

1990 Winter Simulation Conference Proceedings

In this paper the authors present a toolkit of C language functions that can be linked with SIMSCRIPT programs to provide the data communication primitives necessary for distributed simulation. The authors' test case is discussed and some timing data are presented. Additionally metrics used to determine the applicability of the server model decomposition for particular simulations are discussed.

This paper presents a methodology that allows the modeling of distributed discrete-event systems to be used in a single threaded simulation. It is assumed that the distributed system is described by a collection of independent models, one for each component. This is in contrast to distributed simulation where the simulation itself is distributed. We accomplish this task by including all of the models into a single program then simulating the communication network. This concept reduces modeling effort by reusing models, allows for trivial state initialization from hardware, and provides maximum fidelity over single model representation of distributed systems. In addition this paper describes the creation of a software tool that is designed to facilitate the modeling and simulation of distributed systems.

Proceedings of the 28th conference on Winter simulation - WSC '96, 1996

Distributed simulation has proved to be a cost effecti ve technique for studying and understanding complex realworld systems. Many distributed simulations need to incorporate hundreds or even thousands of processors, across both local and wide area networks. As the size and complexity of distributed simulations increase so do the demands on the hardware and software resources that provide simulation services, causing performance bottlenecks that limit the effectiveness of distributed simulation. Different abstractions of performance are needed depending on who is analyzing the distributed simulation and for what reason. This paper proposes a framework for identifying the factors affecting performance and provides a technique for associating the performance factors with high-level system metrics that describe the behavior of the physical and logical resources and services used in the design and implementation of distributed simulations. Dynamic and static analysis of the performance information provides feedback on the execution of the simulation and can provide meaningful information as a guide in making decisions about the configuration and control of the available hardware and software resources for distributed simulation exercises.

2002

This panel paper presents the views of five researchers and practitioners of distributed simulation. Collectively we attempt to address what the implications of distributed simulation are for industry. It is hoped that the views contained herein, and the presentations made by the panelists at the 2002 Winter Simulation Conference will raise awareness and stimulate further discussion on the application of distributed simulation methods and technology in an area that is yet to benefit from the arguable economic benefits that this technique promises.

Proceedings of IFIP-TC6 8-th International Conference on Personal Wireless Communications (PWC'03)., 2003

This position paper introduces the motivation and preliminary implementation issues of a distributed simulation middleware designed to increase the performance and speed-up in the distributed simulation of wireless systems characterized by mobile hosts. Topology changes due to simulated hosts’ mobility map on dynamic causality effects in the ”areas of influence” of each mobile device. We analyze the preliminary definition of a new dynamic mechanism for the runtime management and distributed allocation of model-components executed over a cluster of Physical Execution Units (PEUs). A migration mechanism dynamically adapts the topology changes in the wireless network to a reallocation of model components over the PEUs. The aim is the reduction of communication overheads, between the PEUs, required to distribute the event messages between model components. The distributed simulation framework is based on HLA-compliant runtime infrastructure and preliminary, adaptive load-balancing and migration heuristics.

In this paper we present recent developments in the domain of modeling andsimulation of large scale distributed systems (LSDS).Such systems possessfeatures that include resource sharing,openness,concurrency,scalability,fault-tolerance,and transparency.The use of simulators for evaluatingdifferent methods or techniques designed for such systems is appealing dueto factors such as reduced costs or time,diversity of modeling scenarios,andothers.Recently several simulators where developed to model large scaledistributed systems,considering their particular characteristics.In this work we present an analysis of simulators’ properties,considering their designcharacteristics and the particularities of the used simulation models.Weemphasize the pros and cons for each of the surveyed simulators,andpresent our approach in developing a generic simulator for large scaledistributed systems.We also present a vision for future trends in this domain.

Proceedings of the IEEE FIRB-Perf Workshop on Techniques Methodologies and Tools for Performance Evaluation of Complex Systems (Perf 2005)., 2005

In this work we illustrate the design and implementation guidelines of a recently developed middleware defined to support the parallel and distributed simulation of large scale, complex and dynamically interacting system models. The distributed simulation of complex system models, may suffer the communication and synchronization required to maintain the causality constraints between distributed model components. We designed and implemented the ARTÌS middleware as a new framework by incorporating a set of features that allow adaptive optimization by exploiting many complex and dynamic model and distributed simulation characteristics. As an example, a dynamic migration mechanism for the run-time adaptive allocation of model entities has been designed and exploited for dynamic load and communication balancing. Optimizations have been introduced to obtain the maximum advantage from heterogeneous and asymmetric communication systems, from shared memory to LAN and Internet communication. Other optimizations have been introduced by the exploitation of concurrent replications of parallel and distributed simulations, in order to increase the resources utilization and to maximize the speedup of simulation processes. Solutions have been designed, implemented and tuned to obtain a significant reduction in the communication and synchronization overheads between the physical execution units, and an increased model scalability and simulation speedup, even in worst-case modeling assumptions and simulation scenarios.