Network Modeling and Simu

Mine Communication Sys

N. Moayeri and M. Souryal

May 12, 2011
Disclaimer: The National InsStandards and Technology (Nnot endorse any commercial product mentioned in this pre
Network Modeling and Simulat

 What is it good for?

– Facilitate design and development of c

& networking products.

– Size up, deploy, and configure a comm

network at a particular site to meet perrequirements.

• Connectivity• Quality of Service (QoS)• Network Capacity / Blocking Probability

– Assess fault-tolerance and self-healing 

the network.
Network Modeling and Simulat

 What does it take to do NMS?

– Complete technical specifications of co

devices and networking protocols that 

– Knowing how to use the NMS tool and 

hours; NMS is resource-intensive!

 What are the caveats?

– Fidelity of the models; there will alway

abstraction in any modeling effort.
Types of Modeling and Sim

 For characterizing the communication cha

– e.g. ray tracing for modeling RF chann

 For designing point-to-point communicati

– e.g. MATLAB or SPW for detailed mod

simulation of the physical (PHY) layer

 For assessing the performance of the net

– e.g. OPNET for detailed modeling of th

performance evaluations

 To keep the computational complexity ma

typically not possible to run a simulation tthree components simultaneously and joi
Overview of Simulation S

Radio Specs

Noise Model

Channel 

Propagation 

Model

PHY Layer

Modeler

NMS Tool

BER/PER 

Tables

Ray Tracing Tool 
NMS Tool Componen

 Network Topology Modeler

– mine layout– Initial node positions

 Node Mobility Modeler Traffic Generator

– voice / data / video– constant / variable bit rate (CBR/VBR)

 Network Node Modeler

– models for various layers of the protocol stack 

network, application, etc)

 Performance Evaluation Tools

– performance metrics (packet delivery ratio, de

probability)

 Visualization Tools Support for data archival
Popular NMS Tools

 OPNET

– most commonly used NMS tool– has the largest repository of models

 ns2 / ns3

– free and open source

– initially intended for wired networks; la

wireless models available now

– no extensive visualization aids or tech

 QualNet

– about 10 years old– originally advertised as more scalable 
More on NMS Tools

 In addition to network models that come w

these tools, the user can develop his/her using C/C++.

 It takes some effort to learn how to use a

tools, let alone develop your own models to the tool.
NMS Example

 In 2008-2009, NIST developed models fo

networking solution (secondary communideveloped by Kutta Technologies under oNIOSH and as a result of the 2006 MINE

 Details of this network modeling and simu

given in the next dozen slides along with performance evaluation results.
Medium Frequency Mesh N

• 300 kHz – 3 MHz• Digital communications• Store-and-forward packet transmission
Evolution of Mesh Node M

v. 1

v. 2

Routing AODV Simple Flooding MAC CSMA/CA CSMA/CA 

Modulation QPSK MSK 

FEC RS + CC CC 

Data Rate 30 kb/s 10 kb/s 

Components of mod
Noise/Interference Mod

 Background noise

– Additive white Gaussian noise (AWGN

post-accident scenario

– Electromagnetic interference (EMI)

• Generated by mine machinery• Model for normal operations• More impulsive distribution

 Multiple access interference

– Simultaneous transmissions 

by two or more nodes
Channel Propagation Mo

 MF signal attenuation due to:

– Length of conductor

•

X dB per 305 m (1000 ft) where 3 

≤

– Inductive coupling

• 30-40 dB over 0.305 m (1 foot)• power loss with distance

– Breaks/gaps in conductor

{

4

1

r

NIOSH is currently researching an improved MF prop
Packet Error Rate of Uncoded MSK: 56
Push-to-Talk Voice Traffic Exampl

Time (s)

Hold time ~ lognormal(

m=3.9 s, 

σ=3.3 s)*

Inter-call time 

* D. S. Sharp et. al., "Analysis of Public Safety Traffic on Trunked Land Mobile Ra

Selected Areas in Communications, vol. 22, no. 7, Sept. 2004, pp. 1197-1205.
MF Mesh Network Simulatio

MSK, 37 dBm, 568-bit packets

AWGN, EMI

Radio Specs

Noise Model

Channel 

Propagation 

Model

MATLAB

OPNET

BER/PER 

Tables

Traffic 

Model

Path loss, Inductive coupling loss

PTT: lognormal hold time, exponential inter-call time
OPNET Screenshot: Mobile MF N
MF Static Network Exam

1) Group Comm.: {G,4,5,6}2)

G

↔4 and 5

↔

6

24 dB/1000 ft loss
Group Communication Re

<1% packet loss

G 

→ {4,5,6}

Packets Sent/Received P
Point-to-Point Communicatio

G 

→

4 

Packets Sent/Received

13% packet loss 
NMS for Interoperability T

 One way of achieving interoperability is th

gateways / bridges between the primary asystem(s).

 It is straightforward to develop models for 

bridge nodes and carry out simulations to network performance when the primary slonger available in the aftermath of a min

 Need to know how many such nodes sho

deployed and where.

 Can evaluate various traffic management 

prioritization algorithms.

 Can determine how much storage is need

gateway / bridge for store / forward scena
Extra Slides
Packet Format

Voice (2400 bps codec) T

@ 8 frames/packet @ 48 char

= 48 Bytes = 48 

+ 4-byte application header

+ 9-byte frame overhead

= 61 Bytes

+ 8-byte preamble/sync + 2-byte 

= 71 Bytes (568 bits)

21.8 ms @ 26 kb/s
Bit Error Rate of Uncoded MSK: AW
Mobile MF Node Exam

Comm.: G 

↔

4

24 dB/1000 ft loss
Mobile MF Node Resu

Delay G 

→

4 
Summary of Simulation Cap

 Applications: PTT Voice, Text (unicast an Routing: Simple flooding, AODV, ... PHY modulation: MSK, QPSK, ... PHY FEC: Convolutional, Reed Solomon Channel model:

– Conductor loss, inductive coupling los– AWGN, EMI

 Performance measures: Packet loss, end

throughput, etc.