SimEvents 2.3

Product Description

• Introduction and Key Features
• Working with SimEvents
• Debugging Your Model
• Accessing Statistics
• Interfacing with Simulink and Stateflow

Introduction

SimEvents extends Simulink with a discrete-event simulation (DES) model of computation. With SimEvents you can develop activity-based models of systems to evaluate system parameters such as congestion, resource contention, and processing delays. You can configure entities with user-defined attributes, and then aggregate entities and attributes to model data hierarchy and transport in applications such as packet-based networks, mission planning, supervisory control, real-time operating systems, and computer architecture.

SimEvents works with Stateflow (available separately) to represent systems containing detailed state-transition charts that may produce or be controlled by discrete events. SimEvents and Simulink provide an integrated environment for modeling hybrid dynamic systems containing continuous-time, discrete-time, and discrete-event components. Typical examples occur in communications, automotive, electronic systems, sensor networks, and other distributed control applications.

Far left: A SimEvents model of shared access communications. You can use SimEvents to model background traffic along with specific nodes of interest. Near left: A plot of entity delays showing two simultaneous arrival events. Click on image to see enlarged view.

Key Features

• Enables modeling of system functionality and resource contention in discrete-event simulations
• Provides entity- and token-based modeling capability
• Enables association of dense payloads with entities using vectors and matrices
• Supports algorithm development with Embedded MATLAB™ functions for modifying the payloads/data associated with entities
• Models data hierarchy and synchronization through entity and attribute aggregation
• Provides queues, servers, switches, gates, timers, timeouts, and generators for entities, events, and signals
• Supports hybrid simulation of models that contain both event-based and time-based execution components
• Automatically collects common statistics, such as delay and throughput