Predicting the performance of synchronous discrete event simulation

We develop a model to predict the performance of synchronous discrete event simulation. Our model considers the two most important factors for the performance of synchronous simulation: load balancing and communication. The effect of load balancing in a synchronous simulation is computed using probability distribution models. We derive a formula that computes the cost of synchronous simulation by combining a communication model called LogGP and computation granularity. Even though the formula is simple, it is effective in capturing the most important factors for the synchronous simulation. The formula helps us to predict the maximum speed up achievable by synchronous simulation. In order to examine the prediction model, we have simulated several large ISCAS logic circuits and a simple PCS network simulation on an SGI Origin 2000 and Terascale Computing System (TCS) at the Pittsburgh Supercomputing Center. The results of the experiment show that our performance model accurately predicts the performance of synchronous simulation. The performance model developed is used to analyze the effect of several factors that may improve the performance of synchronous simulation. The factors include problem size, load balancing, granularity, communication overhead, and partitioning.     

Decision support by rapid simulation using simulation nets

The working of a tool, Simulation Nets, for designing and executing models for simulation of systems is presented. The tool is an extension of the theoretically attractive Petri Nets, whose suitability in general simulation modeling has largely been overlooked in the simulation community. Simulation Nets helps in obtaining a correct simulation model because of their good graphical properties, their strength in describing concurrent processes, and because of the possibility in proving correctness for some parts of the model by applying the well known reachability tree technique. The resulting graphical model consists of a number of submodels. The submodels are exact enough to permit simulation experiments to be performed without the need of programming. This permits easy incremental validation of the model, i.e., validation of the submodels and a hierarchy of coupled submodels. Simulation nets thus facilitates rapid modeling and experimentation and thus supports the decision maker in obtaining the data needed for him to make his decision. Experiences with a working prototype are presented.     

Optimising a complex discrete event simulation model using a genetic algorithm

A steelworks model is selected as representative of the stochastic and unpredictable behaviour of a complex discrete event simulation model. The steel-works has a number of different entity or object types. Using the number of each entity type as parameters, it is possible to find better and worse combinations of parameters for various management objectives. A simple real-coded genetic algorithm is presented that optimises the parameters, demonstrating the versatility that genetic algorithms offer in solving hard inverse problems.     

Parallel discrete event simulation using shared memory

With traditional event-list techniques, evaluating a detailed discrete event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments using the Chandy-Misra distributed simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queuing network models.<>     

PL/I as a discrete event simulation tool

The programming language PL/I is considered as a most useful and portable discrete event simulation tool. This paper discusses design facilities required in simulation languages, making use of a model described in PL/I. The problem of queues, parallelism and synchronization in a simulator is solved. The structure of the simulator is considered.     

Validation Challenge Workshop

This special issue presents the results of the Sandia organized Model Validation Challenge Workshop, held May 2006. The workshop brought together researchers from different fields to present various approaches to model validation, and focused on the methodological elements of model validation rather than on model building. Three problems were defined in the disciplines of structural statics, structural dynamics, and heat transfer, all with a uniform structure. The workshop was specifically designed to investigate the relative merits of different approaches to hierarchal model validation through application to these problems. This paper describes a hierarchal approach in the challenge problems, presents the uniform conceptual framework that was used for the challenge problem definitions, and provides an overview of the organization of this special issue.     

Thermal challenge problem: Summary

This paper summarizes the approaches used to address the thermal validation challenge problem. The approaches differ in their characterization of the thermal properties and uncertainty, the definitions and use of validation metrics, the use of validation experimental data to characterize or improve the model predictions, and the assessment of regulatory compliance. All approaches estimated regulatory failure with the resulting estimated probabilities varying by an order of magnitude.     

Efficient autonomic cloud computing using online discrete event simulation

Interest is growing in open source tools that let organizations build IaaS clouds using their own internal infrastructures, alone or in conjunction with external ones. A key component in such private/hybrid clouds is virtual infrastructure management, i.e., the dynamic orchestration of virtual machines, based on the understanding and prediction of performance at scale, with uncertain workloads and frequent node failures. Part of the research community is trying to solve this and other IaaS problems looking to Autonomic Computing techniques, that can provide, for example, better management of energy consumption, quality of service (QoS), and unpredictable system behaviors. In this context, we first recall the main features of the NAM framework devoted to the design of distributed autonomic systems. Then we illustrate the organization and policies of a NAM-based Workload Manager, focusing on one of its components, the Capacity Planner. We show that, when it is not possible to obtain optimal energy-aware plans analytically, sub-optimal plans can be autonomically obtained using online discrete event simulation. Specifically, the proposed approach allows to cope with a broader range of working conditions and types of workloads.     

Domain-specific discrete event modelling and simulation using graph transformation

Graph transformation is being increasingly used to express the semantics of domain-specific visual languages since its graphical nature makes rules intuitive. However, many application domains require an explicit handling of time to accurately represent the behaviour of a real system and to obtain useful simulation metrics to measure throughputs, utilization times and average delays. Inspired by the vast knowledge and experience accumulated by the discrete event simulation community, we propose a novel way of adding explicit time to graph transformation rules. In particular, we take the event scheduling discrete simulation world view and provide rules with the ability to schedule the occurrence of other rules in the future. Hence, our work combines standard, efficient techniques for discrete event simulation (based on the handling of a future event set) and the intuitive, visual nature of graph transformation. Moreover, we show how our formalism can be used to give semantics to other timed approaches and provide an implementation on top of the rewriting logic system Maude.     

Maintaining the validity of simulation models using prediction intervals

This paper presents a methodology for maintaining the operational validity of simulation models of observable systems in order to support operational decisions. In this methodology, real-time system data are continuously compared against simultaneous prediction intervals on selected responses constructed using the simulation model. The methodology is illustrated through using a case example of a simulation model of a flexible manufacturing system. Different invalidating discrepancies between the model and the system are investigated. Results indicate that using nontraditional responses may lead to a faster detection of invalidating changes, the speed of detection is a function of the scope of the change, and the model may evolve with the system and continue to be used to guard against random changes.     

The evolution of a new discrete event simulation language for inexperienced users (WIDES)

This paper describes the evolution and use of the Wisconsin Discrete Event Simulator (WIDES). WIDES is a GASP-based collection of ANSI FORTRAN subroutines and data structures designed as a discrete event simulation language for use on small machines by inexperienced users in an educational environment. A list of criteria for selection of a language for such use is presented. These criteria include considerations and constraints in areas such as the language's modelling capabilities, its programming ease, storage requirements, educational features, cost and availability. Among commonly available languages only GASP meets the postulated storage constraints. Unfortunately, this language exhibits a lacklustre performance in the other performance areas, and in our experience it is not an ideal language for the above-stated audience and environment. However, GASP is based on a sound design, and it is extremely well implemented; thus, GASP was chosen as the basis for the development of a new language that meets the criteria stated above. This development is presented here. The resulting language is briefly presented and an example of its use is given. Program listings, users' guides and sample problems are available from the author.     

Parallel discrete event simulation with SIMULA

The area of Discrete Event Simulation (DES) is the least impacted by parallel processing even though most of its applications require tremendous amounts of processing time. The common approach of parallelizing individually special purpose programs leads to very limited improvements in performance. We propose here the parallelization of general DES applications written in SIMULA, as a part of an ongoing project that aims towards developing methodologies and architectures for parallel DES. SIMULA is a general purpose process oriented language whose structure allows the creation of processes which can participate in a quasi-parallel execution according to an interleaved fashion. Problems related to the process interference representation, parallel scheduling and process synchronization are defined and solved. To test and verify the theoretical results the parallel execution of experimental and real DES applications has been simulated. The results show that significant improvement in performance can be expected.     

Using Ada for discrete event simulation

The process interaction approach is proposed for developing a discrete simulation environment in Ada. The introduction of simulation facilities in Ada not only concerns the classical aspect of model building, but allows a new class of problems to be tackled, that is the testing of correctness of programs intended for real-time applications. In this paper attention is focused on the presentation of the process scheduling in the simulation context and on the definition of standard forms of interactions among processes. Simulation facilities are organized by making use of Ada's structuring concepts.     

Analysis of the resilience of team performance during a nuclear emergency response exercise

The current work presents results from a cognitive task analysis (CTA) of a nuclear disaster simulation. Audio-visual records were collected from an emergency room team composed of individuals from 26 different agencies as they responded to multiple scenarios in a simulated nuclear disaster. This simulation was part of a national emergency response training activity for a nuclear power plant located in a developing country. The objectives of this paper are to describe sources of resilience and brittleness in these activities, identify cues of potential improvements for future emergency simulations, and leveraging the resilience of the emergency response system in case of a real disaster. Multiple CTA techniques were used to gain a better understanding of the cognitive dimensions of the activity and to identify team coordination and crisis management patterns that emerged from the simulation exercises.     

Modeling discrete event scalable network systems

Scalability in simulation tools is one of the most important traits to measure performance of software. The reason is that today’s Internet is the main instance of a large-scale and highly complex system. Simulation of Internet-scale network systems has to be supported by any simulation tool. Despite this fact, many network simulators lacks support for building large models. In this work, in order to propose a new approach for scalability issue in network simulation tools, a network simulator is developed based on behavior of honeybees and high performance DEVS, modular and hierarchical system theoretic approach. A biologically-inspired discrete event modeling approach is described for studying networks’ scalability and performance traits. Since natural systems can offer important concepts for modeling network systems, key adaptive and emergent attributes of honeybees and their societal properties are incorporated into a set of simulation models that are developed using the discrete event system specification approach. Large-scale network models are simulated and evaluated to show the benefits of nature-inspired network models.     

Predicting the behavior of large scale P2P systems by parallel discrete event simulation

P2P systems are becoming the dominator of Internet.Such systems are typically composed of thousands to millions of physical computers,which make it difficult to predict their behaviors without a large scale distributed system simulator.This paper is an attempt to predict the behavior of large scale P2P systems by building a novel parallel simulator:AegeanSim,which provides parallel discrete event simulation of such systems on high performance server clusters.We abstract the execution of P2P applications wit...     

基于乐观策略的并行离散事件模拟研究

并行离散事件模拟（PDES）又称分布式模拟,通过将一个离散事件模拟程序在多个处理器上并行执行来提高模拟性能。乐观策略在解决并行模拟中各模拟部分之间的同步关系时具有较好的性能。介绍了基于乐观策略的并行离散事件模拟的原理,讨论了存在的问题,并给出相应的解决方法。     

Formulation of the thermal problem

This paper describes the thermal problem and presents the experimental data for validation. The thermal problem involves validating a model for heat conduction in a solid. The mathematical model is based on one-dimensional, linear heat conduction in a solid slab, with heat flux boundary conditions. Experimental data from a series of material characterization, validation, and accreditation experiments related to the mathematical model are provided. The objective is to use the series of experiments to assess the model, and then use the model to predict regulatory performance relative to a regulatory requirement. The regulatory requirement is defined in terms of the probability that a surface temperature not exceed a specified temperature at the regulatory conditions.     

Web Services with generic simulation models for discrete event simulation

Today the Internet and the World Wide Web (WWW) are on the cusp of a paradigm shift. Up to now most actions in the WWW are sorts of human–computer interaction, but the introduction of the eXtensible Markup Language (XML) changed the perception. The Internet will be seen as a great space of information and with the use of XML and following technologies like Web Services, Grid Computing and Semantic Web the difference between human–machine interaction and machine–machine interaction vanishes. This work investigates the usefulness of XML in the simulation domain and uses Web Service technology to build the SimASP framework for discrete event simulation (DES).