scholarly journals Exploring the model development process in discrete-event simulation: insights from six expert modellers

2015 ◽  
Vol 66 (5) ◽  
pp. 747-760 ◽  
Author(s):  
Antuela A Tako
Keyword(s):  
Discrete Event Simulation ◽  
Development Process ◽  
Discrete Event ◽  
Model Development ◽  
Event Simulation ◽  
Model Development Process

Modeling and Simulation of IEEE 802.11 Wireless LANs

2012 ◽  
pp. 85-99 ◽  
Author(s):  
Nurul I. Sarkar ◽  
Roger McHaney
Keyword(s):  
Modeling And Simulation ◽  
Ieee 802.11 ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Model Development ◽  
Local Area ◽  
Network Simulator ◽  
Event Simulation ◽  
802.11 Wireless Lans ◽  
And Performance

Stochastic discrete event simulation methodology is becoming increasingly popular among network researchers worldwide in recent years. This popularity results from the availability of various sophisticated and powerful simulation software packages, and also because of the flexibility in model construction and validation offered by simulation. In this chapter, the authors describe their experience in using the network simulator 2 (ns-2), a discrete event simulation package, as an aid to modeling and simulation of the IEEE 802.11 Wireless Local Area Networks (WLANs). This chapter provides an overview of ns-2 focusing on simulation environment, architecture, model development and parameter setting, model validation, output data collection and processing, and simulation execution. The strengths and weaknesses of ns-2 are discussed. This chapter also emphasizes that selecting a good simulator is crucial in modeling and performance analysis of wireless networks.

scholarly journals Pengembangan Simulasi Kejadian Diskret Berbasis Paket Simmer pada R

2021 ◽  
Vol 3 (2) ◽  
pp. 79-85
Author(s):  
I G.A. Anom Yudistira
Keyword(s):  
Simulation Model ◽  
Discrete Event Simulation ◽  
Model Building ◽  
Discrete Event ◽  
Model Development ◽  
Complex Form ◽  
Literature Study ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Complex Forms

This study aims to describe the various capabilities of the simmer package on R, especially in running a discrete event simulation model, then develop a DES simulation model building technique, which is effective and can represent real systems well, and explore the simulation output on this simmer, both in statistical summary form and parameter estimation. The method used in this research is the literature study, with descriptive and exploratory approaches. Model development is more effective when it is carried out starting from simple models, to more complex forms step by step, and describing the system using a flow chart. Replication for simulations is easy to perform, so as to get standard error values ​​for model parameter estimators. The stages in developing a discrete event simulation model with a simmer, start with compiling a simple flowchart to a more complex form, and replication is carried out. The simmer output in the form of data.frame makes it very easy to further process the output. The simple R API on simmer will also make it easier to simulate

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