SlideShare a Scribd company logo
1 of 13
What is ns? 
 Object-oriented, discrete event driven network 
simulator 
 It was normally used in wired & wireless protocol 
 Written in C++ and OTcl
ADVANTAGES 
1. Debugging of errors makes easy, 
2. It is cheap doesnot not require any equipment, 
3. Even an complex scenario can be tested effiently.
ns Architecture 
Tcl 
OTcl 
TclCL 
ns-2 
Event 
Scheduler 
Network 
Components 
C/C++
Simulation Network 
Wired Network 
Routing: Distance Vector, Link State 
Transportation: TCP and UDP 
Queuing disciplines: drop-tail 
Wireless 
Ad-hoc routing and mobile IP: AODV 
Sensor-MAC, WiMAX (new) 
Power control in wireless networks
NS2 Functionalities 
Traffic models and applications 
◦ FTP, CBR 
Transport protocols 
◦ Unicast: TCP, UDP 
Routing and queuing 
◦ Wired and ad-hoc routing 
◦ Queuing protocols: drop-tail, etc 
Physical media 
◦ Wired (point-to-point, LANs), wireless (multiple 
propagation models), satellite
Ns – structure 
Types 
1. Event Schedular 
2. Turn on Tracing 
3. Network Topology 
4.Transport Connection 
5. Generate Traffic 
6.Start Simulation
Attaching Transport 
Agents to Nodes-tcp/udp 
TCP : 
set src [new Agent/TCP/FullTcp] 
set sink [new Agent/TCP/FullTcp] 
$ns_ attach-agent $node_(s1) $src 
$ns_ attach-agent $node_(k1) $sink 
$ns_ connect $src $sink
Udp agent 
Set udp0 [new Agent/Null] 
ns attach-agent $n0 $udp0 
set cbr0 [new Application/Traffic/CBR] 
$cbr0 attach-agent $udp0 
$udp0 set packetSize_ 536 ; #(max=1000) 
set null0 [new Agent/Null] 
$ns attach-agent $n1 $null0 
$ns connect $udp0 $null0
PACKETS 
It is the collection of data,whether header is called or not all 
header files where present in the stack registers. 
Cmn header 
Ip header 
Tcp header 
Rtp header 
Trace header 
Header 
data
Trace Analysis 
Trace packets on individual link 
Tracefile format:
NAM 
ns has a companion network animator called nam 
hence, has been called the nsnam project
Xgraph 
 One part of the ns-allinone package is 'xgraph', a 
plotting program which can be used to create graphic 
representations of simulation results.

More Related Content

What's hot

Building blocks for aggregate programming of self-organising applications
Building blocks for aggregate programming of self-organising applicationsBuilding blocks for aggregate programming of self-organising applications
Building blocks for aggregate programming of self-organising applicationsFoCAS Initiative
 
Cassandra at talkbits
Cassandra at talkbitsCassandra at talkbits
Cassandra at talkbitsMax Alexejev
 
In class, we discussed min-heaps. In a min-heap the element of the heap with ...
In class, we discussed min-heaps. In a min-heap the element of the heap with ...In class, we discussed min-heaps. In a min-heap the element of the heap with ...
In class, we discussed min-heaps. In a min-heap the element of the heap with ...licservernoida
 
[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...
[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...
[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...PROIDEA
 
Easily reduce runtimes with cython
Easily reduce runtimes with cythonEasily reduce runtimes with cython
Easily reduce runtimes with cythonMichal Mucha
 
Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...
Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...
Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...InfluxData
 
Time Series Data with InfluxDB
Time Series Data with InfluxDBTime Series Data with InfluxDB
Time Series Data with InfluxDBTuri, Inc.
 
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian ApproachAutomatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian ApproachSpark Summit
 
Devry gsp 215 week 6 i lab virtual memory new
Devry gsp 215 week 6 i lab virtual memory newDevry gsp 215 week 6 i lab virtual memory new
Devry gsp 215 week 6 i lab virtual memory newwilliamethan912
 
Artificial Neural Networks for Storm Surge Prediction in North Carolina
Artificial Neural Networks for Storm Surge Prediction in North CarolinaArtificial Neural Networks for Storm Surge Prediction in North Carolina
Artificial Neural Networks for Storm Surge Prediction in North CarolinaAnton Bezuglov
 
Deccan RubyConf 2016 - Lighning Talk - SpiceRub
Deccan RubyConf 2016 - Lighning Talk - SpiceRubDeccan RubyConf 2016 - Lighning Talk - SpiceRub
Deccan RubyConf 2016 - Lighning Talk - SpiceRubGaurav Tamba
 
Ch 5: Introduction to heap overflows
Ch 5: Introduction to heap overflowsCh 5: Introduction to heap overflows
Ch 5: Introduction to heap overflowsSam Bowne
 
The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015
The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015
The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015Johan
 
Secondary Spectrum Usage for Mobile Devices
Secondary Spectrum Usage for Mobile DevicesSecondary Spectrum Usage for Mobile Devices
Secondary Spectrum Usage for Mobile DevicesAmjed Majid
 

What's hot (18)

JavaCro'15 - Big Data in a DIY home - Marko Švaljek
JavaCro'15 - Big Data in a DIY home - Marko ŠvaljekJavaCro'15 - Big Data in a DIY home - Marko Švaljek
JavaCro'15 - Big Data in a DIY home - Marko Švaljek
 
Building blocks for aggregate programming of self-organising applications
Building blocks for aggregate programming of self-organising applicationsBuilding blocks for aggregate programming of self-organising applications
Building blocks for aggregate programming of self-organising applications
 
C07.heaps
C07.heapsC07.heaps
C07.heaps
 
Cassandra at talkbits
Cassandra at talkbitsCassandra at talkbits
Cassandra at talkbits
 
In class, we discussed min-heaps. In a min-heap the element of the heap with ...
In class, we discussed min-heaps. In a min-heap the element of the heap with ...In class, we discussed min-heaps. In a min-heap the element of the heap with ...
In class, we discussed min-heaps. In a min-heap the element of the heap with ...
 
Advanced R Graphics
Advanced R GraphicsAdvanced R Graphics
Advanced R Graphics
 
[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...
[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...
[4DEV][Łódź] Ivan Vaskevych - InfluxDB and Grafana fighting together with IoT...
 
Easily reduce runtimes with cython
Easily reduce runtimes with cythonEasily reduce runtimes with cython
Easily reduce runtimes with cython
 
Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...
Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...
Meet the Experts: Visualize Your Time-Stamped Data Using the React-Based Gira...
 
Time Series Data with InfluxDB
Time Series Data with InfluxDBTime Series Data with InfluxDB
Time Series Data with InfluxDB
 
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian ApproachAutomatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
 
Devry gsp 215 week 6 i lab virtual memory new
Devry gsp 215 week 6 i lab virtual memory newDevry gsp 215 week 6 i lab virtual memory new
Devry gsp 215 week 6 i lab virtual memory new
 
Artificial Neural Networks for Storm Surge Prediction in North Carolina
Artificial Neural Networks for Storm Surge Prediction in North CarolinaArtificial Neural Networks for Storm Surge Prediction in North Carolina
Artificial Neural Networks for Storm Surge Prediction in North Carolina
 
Deccan RubyConf 2016 - Lighning Talk - SpiceRub
Deccan RubyConf 2016 - Lighning Talk - SpiceRubDeccan RubyConf 2016 - Lighning Talk - SpiceRub
Deccan RubyConf 2016 - Lighning Talk - SpiceRub
 
Ch 5: Introduction to heap overflows
Ch 5: Introduction to heap overflowsCh 5: Introduction to heap overflows
Ch 5: Introduction to heap overflows
 
Quantum computers
Quantum computersQuantum computers
Quantum computers
 
The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015
The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015
The Directions Pipeline at Mapbox - AWS Meetup Berlin June 2015
 
Secondary Spectrum Usage for Mobile Devices
Secondary Spectrum Usage for Mobile DevicesSecondary Spectrum Usage for Mobile Devices
Secondary Spectrum Usage for Mobile Devices
 

Viewers also liked

H Mεσογειακή Διατροφή στον τόπο μου
H Mεσογειακή Διατροφή στον τόπο μουH Mεσογειακή Διατροφή στον τόπο μου
H Mεσογειακή Διατροφή στον τόπο μουMaria Louvari
 
Gathering Information & Scanning Environment
Gathering Information & Scanning EnvironmentGathering Information & Scanning Environment
Gathering Information & Scanning EnvironmentJealene Bautista
 
Глянец №26 (июль-август 2014)
Глянец №26 (июль-август 2014)Глянец №26 (июль-август 2014)
Глянец №26 (июль-август 2014)Nina Timina
 
Buku Tata Kelola Internet
Buku Tata Kelola InternetBuku Tata Kelola Internet
Buku Tata Kelola InternetID-IGF
 
Журнал "Глянец" №2 (март-апрель 2011)
Журнал "Глянец" №2 (март-апрель 2011)Журнал "Глянец" №2 (март-апрель 2011)
Журнал "Глянец" №2 (март-апрель 2011)Nina Timina
 
Agenda Acara National ID-IGF Dialogue 2014
Agenda Acara National ID-IGF Dialogue 2014Agenda Acara National ID-IGF Dialogue 2014
Agenda Acara National ID-IGF Dialogue 2014ID-IGF
 
Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...
Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...
Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...Meghan Lee
 
Presentación Cacytmar_ejemplo para curso slideshare uca
Presentación Cacytmar_ejemplo para curso slideshare ucaPresentación Cacytmar_ejemplo para curso slideshare uca
Presentación Cacytmar_ejemplo para curso slideshare ucapatricia2006
 
Network simulator 2
Network simulator 2Network simulator 2
Network simulator 2AAKASH S
 

Viewers also liked (17)

H Mεσογειακή Διατροφή στον τόπο μου
H Mεσογειακή Διατροφή στον τόπο μουH Mεσογειακή Διατροφή στον τόπο μου
H Mεσογειακή Διατροφή στον τόπο μου
 
Buildings
BuildingsBuildings
Buildings
 
Gathering Information & Scanning Environment
Gathering Information & Scanning EnvironmentGathering Information & Scanning Environment
Gathering Information & Scanning Environment
 
Глянец №26 (июль-август 2014)
Глянец №26 (июль-август 2014)Глянец №26 (июль-август 2014)
Глянец №26 (июль-август 2014)
 
Buku Tata Kelola Internet
Buku Tata Kelola InternetBuku Tata Kelola Internet
Buku Tata Kelola Internet
 
Журнал "Глянец" №2 (март-апрель 2011)
Журнал "Глянец" №2 (март-апрель 2011)Журнал "Глянец" №2 (март-апрель 2011)
Журнал "Глянец" №2 (март-апрель 2011)
 
Hxc12
Hxc12Hxc12
Hxc12
 
Hxc11
Hxc11Hxc11
Hxc11
 
Agenda Acara National ID-IGF Dialogue 2014
Agenda Acara National ID-IGF Dialogue 2014Agenda Acara National ID-IGF Dialogue 2014
Agenda Acara National ID-IGF Dialogue 2014
 
Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...
Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...
Closing Achievement Gaps in U.S. Public Schools: Exploring Global Models of L...
 
Kuldeep Singh
Kuldeep SinghKuldeep Singh
Kuldeep Singh
 
P18aspects2impacts (1)
P18aspects2impacts (1)P18aspects2impacts (1)
P18aspects2impacts (1)
 
Presentación Cacytmar_ejemplo para curso slideshare uca
Presentación Cacytmar_ejemplo para curso slideshare ucaPresentación Cacytmar_ejemplo para curso slideshare uca
Presentación Cacytmar_ejemplo para curso slideshare uca
 
Hack x Crack N.19
Hack x Crack N.19Hack x Crack N.19
Hack x Crack N.19
 
Network simulator 2
Network simulator 2Network simulator 2
Network simulator 2
 
Hack x Crack N.2
Hack x Crack N.2Hack x Crack N.2
Hack x Crack N.2
 
Data analysis
Data analysisData analysis
Data analysis
 

Similar to Network simulator 2 (20)

Network simulator 2
Network simulator 2Network simulator 2
Network simulator 2
 
Tut hemant ns2
Tut hemant ns2Tut hemant ns2
Tut hemant ns2
 
Ns fundamentals 1
Ns fundamentals 1Ns fundamentals 1
Ns fundamentals 1
 
Ns2
Ns2Ns2
Ns2
 
Ns 2 Network Simulator An Introduction
Ns 2 Network Simulator An IntroductionNs 2 Network Simulator An Introduction
Ns 2 Network Simulator An Introduction
 
Ns network simulator
Ns network simulatorNs network simulator
Ns network simulator
 
cscn1819.pdf
cscn1819.pdfcscn1819.pdf
cscn1819.pdf
 
NS2-tutorial.ppt
NS2-tutorial.pptNS2-tutorial.ppt
NS2-tutorial.ppt
 
Ns2
Ns2Ns2
Ns2
 
Ns2pre
Ns2preNs2pre
Ns2pre
 
NS2-tutorial.pdf
NS2-tutorial.pdfNS2-tutorial.pdf
NS2-tutorial.pdf
 
Introduction to ns2
Introduction to ns2Introduction to ns2
Introduction to ns2
 
Ns2 introduction 2
Ns2 introduction 2Ns2 introduction 2
Ns2 introduction 2
 
~Ns2~
~Ns2~~Ns2~
~Ns2~
 
study-of-network-simulator.pdf
study-of-network-simulator.pdfstudy-of-network-simulator.pdf
study-of-network-simulator.pdf
 
Plenzogan technology
Plenzogan technologyPlenzogan technology
Plenzogan technology
 
Network Simulator Tutorial
Network Simulator TutorialNetwork Simulator Tutorial
Network Simulator Tutorial
 
NS2 (1).docx
NS2 (1).docxNS2 (1).docx
NS2 (1).docx
 
Network simulator 2 a simulation tool for linux
Network simulator 2 a simulation tool for linuxNetwork simulator 2 a simulation tool for linux
Network simulator 2 a simulation tool for linux
 
Ns2
Ns2Ns2
Ns2
 

More from AAKASH S

Detecting of routng misbehavion in hybrid wireless networks used and acknowle...
Detecting of routng misbehavion in hybrid wireless networks used and acknowle...Detecting of routng misbehavion in hybrid wireless networks used and acknowle...
Detecting of routng misbehavion in hybrid wireless networks used and acknowle...AAKASH S
 
A secure qos distributed routing protocol for hybrid wireless networks
A secure qos distributed routing protocol for hybrid wireless networksA secure qos distributed routing protocol for hybrid wireless networks
A secure qos distributed routing protocol for hybrid wireless networksAAKASH S
 
Enhanced Adaptive ACKnowledgment (EAACK)
Enhanced Adaptive ACKnowledgment (EAACK)Enhanced Adaptive ACKnowledgment (EAACK)
Enhanced Adaptive ACKnowledgment (EAACK)AAKASH S
 
A SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKS
A SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKSA SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKS
A SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKSAAKASH S
 
Intrusion detection system
Intrusion detection systemIntrusion detection system
Intrusion detection systemAAKASH S
 
QOD PHASE-1 FINAL PPT
QOD PHASE-1 FINAL PPTQOD PHASE-1 FINAL PPT
QOD PHASE-1 FINAL PPTAAKASH S
 
QOD routing protocols : phase 1 ppt
QOD routing  protocols : phase 1 pptQOD routing  protocols : phase 1 ppt
QOD routing protocols : phase 1 pptAAKASH S
 
Qo s oriented distributed routing protocols : anna university 2nd review ppt
Qo s   oriented  distributed routing  protocols : anna university 2nd review pptQo s   oriented  distributed routing  protocols : anna university 2nd review ppt
Qo s oriented distributed routing protocols : anna university 2nd review pptAAKASH S
 
CP7301 Software Process and Project Management notes
CP7301 Software Process and Project Management   notesCP7301 Software Process and Project Management   notes
CP7301 Software Process and Project Management notesAAKASH S
 
Capability Maturity Model Integration
Capability Maturity Model IntegrationCapability Maturity Model Integration
Capability Maturity Model IntegrationAAKASH S
 
OSI model (7 LAYER )
OSI model (7 LAYER )OSI model (7 LAYER )
OSI model (7 LAYER )AAKASH S
 
A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...
A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...
A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...AAKASH S
 
AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...
AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...
AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...AAKASH S
 
Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...
Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...
Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...AAKASH S
 
Hybrid wireless network -0th review
Hybrid wireless network -0th review Hybrid wireless network -0th review
Hybrid wireless network -0th review AAKASH S
 

More from AAKASH S (15)

Detecting of routng misbehavion in hybrid wireless networks used and acknowle...
Detecting of routng misbehavion in hybrid wireless networks used and acknowle...Detecting of routng misbehavion in hybrid wireless networks used and acknowle...
Detecting of routng misbehavion in hybrid wireless networks used and acknowle...
 
A secure qos distributed routing protocol for hybrid wireless networks
A secure qos distributed routing protocol for hybrid wireless networksA secure qos distributed routing protocol for hybrid wireless networks
A secure qos distributed routing protocol for hybrid wireless networks
 
Enhanced Adaptive ACKnowledgment (EAACK)
Enhanced Adaptive ACKnowledgment (EAACK)Enhanced Adaptive ACKnowledgment (EAACK)
Enhanced Adaptive ACKnowledgment (EAACK)
 
A SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKS
A SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKSA SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKS
A SECURE QOS ROUTING PROTCOL FOR HYBRID WIRELESS NETWORKS
 
Intrusion detection system
Intrusion detection systemIntrusion detection system
Intrusion detection system
 
QOD PHASE-1 FINAL PPT
QOD PHASE-1 FINAL PPTQOD PHASE-1 FINAL PPT
QOD PHASE-1 FINAL PPT
 
QOD routing protocols : phase 1 ppt
QOD routing  protocols : phase 1 pptQOD routing  protocols : phase 1 ppt
QOD routing protocols : phase 1 ppt
 
Qo s oriented distributed routing protocols : anna university 2nd review ppt
Qo s   oriented  distributed routing  protocols : anna university 2nd review pptQo s   oriented  distributed routing  protocols : anna university 2nd review ppt
Qo s oriented distributed routing protocols : anna university 2nd review ppt
 
CP7301 Software Process and Project Management notes
CP7301 Software Process and Project Management   notesCP7301 Software Process and Project Management   notes
CP7301 Software Process and Project Management notes
 
Capability Maturity Model Integration
Capability Maturity Model IntegrationCapability Maturity Model Integration
Capability Maturity Model Integration
 
OSI model (7 LAYER )
OSI model (7 LAYER )OSI model (7 LAYER )
OSI model (7 LAYER )
 
A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...
A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...
A QoS oriented distributed routing protocol for Hybrid Wireless Network :Firs...
 
AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...
AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...
AASR Authenticated Anonymous Secure Routing for MANETs in Adversarial Environ...
 
Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...
Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...
Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replica...
 
Hybrid wireless network -0th review
Hybrid wireless network -0th review Hybrid wireless network -0th review
Hybrid wireless network -0th review
 

Network simulator 2

  • 1.
  • 2. What is ns?  Object-oriented, discrete event driven network simulator  It was normally used in wired & wireless protocol  Written in C++ and OTcl
  • 3. ADVANTAGES 1. Debugging of errors makes easy, 2. It is cheap doesnot not require any equipment, 3. Even an complex scenario can be tested effiently.
  • 4. ns Architecture Tcl OTcl TclCL ns-2 Event Scheduler Network Components C/C++
  • 5. Simulation Network Wired Network Routing: Distance Vector, Link State Transportation: TCP and UDP Queuing disciplines: drop-tail Wireless Ad-hoc routing and mobile IP: AODV Sensor-MAC, WiMAX (new) Power control in wireless networks
  • 6. NS2 Functionalities Traffic models and applications ◦ FTP, CBR Transport protocols ◦ Unicast: TCP, UDP Routing and queuing ◦ Wired and ad-hoc routing ◦ Queuing protocols: drop-tail, etc Physical media ◦ Wired (point-to-point, LANs), wireless (multiple propagation models), satellite
  • 7. Ns – structure Types 1. Event Schedular 2. Turn on Tracing 3. Network Topology 4.Transport Connection 5. Generate Traffic 6.Start Simulation
  • 8. Attaching Transport Agents to Nodes-tcp/udp TCP : set src [new Agent/TCP/FullTcp] set sink [new Agent/TCP/FullTcp] $ns_ attach-agent $node_(s1) $src $ns_ attach-agent $node_(k1) $sink $ns_ connect $src $sink
  • 9. Udp agent Set udp0 [new Agent/Null] ns attach-agent $n0 $udp0 set cbr0 [new Application/Traffic/CBR] $cbr0 attach-agent $udp0 $udp0 set packetSize_ 536 ; #(max=1000) set null0 [new Agent/Null] $ns attach-agent $n1 $null0 $ns connect $udp0 $null0
  • 10. PACKETS It is the collection of data,whether header is called or not all header files where present in the stack registers. Cmn header Ip header Tcp header Rtp header Trace header Header data
  • 11. Trace Analysis Trace packets on individual link Tracefile format:
  • 12. NAM ns has a companion network animator called nam hence, has been called the nsnam project
  • 13. Xgraph  One part of the ns-allinone package is 'xgraph', a plotting program which can be used to create graphic representations of simulation results.