An introduction to simulation of risk processes

A typical model for insurance risk, the so-called collective risk model, has two main components: one characterizing the frequency (or incidence) of events and another describing the severity (or size or amount) of gain or loss resulting from the occurrence of an event. Here we focus on simulating the point process N(t) of the incidence of events. We discuss five prominent examples of N(t), namely the classical (homogeneous) Poisson process, the non-homogeneous Poisson process, the mixed Poisson process, the Cox process (also called the doubly stochastic Poisson process) and the renewal process.Collective risk model; Poisson process; Non-homogeneous Poisson process; Mixed Poisson process; Cox process; Renewal process;

An Introduction to Simulation-Based Techniques for Automated Service Composition

This work is an introduction to the author's contributions to the SOC area, resulting from his PhD research activity. It focuses on the problem of automatically composing a desired service, given a set of available ones and a target specification. As for description, services are represented as finite-state transition systems, so to provide an abstract account of their behavior, seen as the set of possible conversations with external clients. In addition, the presence of a finite shared memory is considered, that services can interact with and which provides a basic form of communication. Rather than describing technical details, we offer an informal overview of the whole work, and refer the reader to the original papers, referenced throughout this work, for all details

As simple as possible, but no simpler: A gentle introduction to simulation modeling

Proceedings of the 2006 Winter Simulation Conference, 1-10.SEED Center PaperWe start with basic terminology and concepts of modeling, and decompose the art of modeling as a process. This overview of the process helps clarify when we should or should not use simulation models. We discuss some common missteps made by many inexperienced modelers, and propose a concrete approach for avoiding those mistakes. After a quick review of event graphs, which are a very straightforward notation for discrete event systems, we illustrate how an event graph can be translated quite directly to a computer program with the aid of a surprisingly simple library. The resulting programs are easy to implement and computationally are extremely efficient. The first half of the paper focuses principles of modeling, should be of general interest. The second half will be of interest to students, teachers, and readers who wish to know how simulations models work and how to implement them from the ground up

CS 470/670: Systems Simulation

Introduction to simulation and comparison with other techniques. Discrete simulation models. Introduction to queuing theory and stochastic processes. Comparison of simulation languages. Simulation methodology and selected applications

Simulation for Cybersecurity: State of the Art and Future Directions

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans in cybersecurity research. The proposed way forward section posits that the advancement of collecting and accessing sociotechnological data to inform models, the creation of new theoretical constructs, and the integration and improvement of behavioral models are needed to advance cybersecurity efforts

Crew station research and development facility training for the light helicopter demonstration/validation program

The U.S. Army Crew Station Research and Development Branch (CSRDB) of the Aircraft Simulation Division (AVSCOM) was tasked by the Light Helicopter Program Manager (LH-PM) to provide training to Army personnel in advanced aircraft simulation technology. The purpose of this training was to prepare different groups of pilots to support and evaluate two contractor simulation efforts during the Demonstration/Validation (DEM/VAL) phase of the LH program. The personnel in the CSRDB developed mission oriented training programs to accomplish the objectives, conduct the programs, and provide guidance to army personnel and support personnel throughout the DEM/VAL phase