Project and labs - LTHomikron.eit.lth.se/ETSN01/ETSN01/tutorials/Tutorial1.pdf · along with the...
Transcript of Project and labs - LTHomikron.eit.lth.se/ETSN01/ETSN01/tutorials/Tutorial1.pdf · along with the...
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Project and labsETSN01 Advanced Telecommunication
Antonio franco
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Antonio Franco
•[email protected]•http://www.eit.lth.se/personal/antonio.franco•Room 3124b, E-building, Ole Römers väg 3
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Outline
•Labs outline•Statistics: a brief review•Labs contents•The final project•Materials on the internet•Tutorials
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Labs organization
•Labs will be 3 hours long and are offered to you in order tofamiliarize yourself with Omnet++, the suite we will use forsimulating different scenarios, that is advised you use forthe simulation part of your final project (already available onthe course homepage);•Labs are not structured as a series of exercises, but willresemble more a walkthrough; I will be available there tohelp you and answer your questions
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Labs software
•In the labs we will use Omnet++ (http://www.omnetpp.org/)along with the MiXiM framework(http://mixim.sourceforge.net/)•If you wish to install the lab software in your computer,please refer to the installation manual you can find in the/docs folder of the Omnet++ archive•Different projects will be released for your simulations forthe three different labs
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Statistics: a brief review
•Probability Density Functions (PDFs)•Confidence intervals•Generate random variables: Inverse transform sampling
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Probability Density Functions
•A PDF is, essentially, a normalized histogram of theoccurrences of a number of experiments, when the numberof experiments goes to infinity.
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Confidence intervals (1)
•We usually approximate the mean of our distribution usingthe samples we have.•Confidence interval answers to the question: ”How far isthe true mean from my approximated mean?”
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Confidence intervals (2)
”True” mean
Estimated mean
Variance
Number of samples
Coefficient for the 95% confidence
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Generate random variables: Inversetransform sampling
•If you have a random number generator following theuniform distribution, you can always generate otherdistributions.
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Lab contents
•Lab1 – TDMA•Lab2 – Random access protocols•Lab3 – Queuing disciplines
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Single server system stability
Arrivalrate Service
rate
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TDMA
• TDMA stands for Time Division Multiple Access• subdivides time into slots, that are assigned to
different agents (devices, flows, etc) in someway (centralized polling, autonomousdecentralized decision, etc)
• We will concentrate on a roundrobinassignment, i.e. the first slot goes to the "first``device , the second to the "second'' etc., andthen the schema is repeated indefinitely
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TDMA systems stability (1)
= ∗< [ ]< [ ]
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TDMA systems stability (2)
•Notice that as Tslot increases, also the time between two slots increases,and so delay per frame increases;•Be aware that Tslot must ensure that the transmission of a single framesucceeds inside one slot time (we will not consider frame fragmentationin our labs), so, if R is the raw data rate of the channel in bps and Bmin isthe minimum frame size in bit, in order to avoid overlaps, it must be:>
< < [ ]
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Random access Schemes
• Random access schemes on the contrast, do notforce devices to access in predetermined slots ortimes;
• Is difficult to find a stability rule for them, and mostlyone relies on simulations in order to dimension arandom access network;
• They are better than TDMA in case of nondeterministic sporadic traffic;
• On the contrary they tend to behave badly in case ofa cramped network;
• Ensuring QoS is difficult;
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Random access Schemes – 802.11 DCFExample
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The final project (1)
•The final project is already online;•It comprises a theoretical part and a simulation part;•You can use either the code provided during the labs,either implement it by yourself;•Is not necessary to simulate the whole scenario, theimportant thing is that you will be able to draw your ownconclusions from the simulation outcome;•Remember: always present plots along withCONFIDENCE INTERVALS (very important!);
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The final project (2)
• You can use whatever tool you want to plot your data, for example:• Excel
(http://omikron.eit.lth.se/ETSN01/ETSN012013/Material_files/confexcel.pdf)
• Matlab® by using the errorbar function (more in the Matlabreference manual -http://se.mathworks.com/help/matlab/ref/errorbar.html)
• Matplotlib (python) by using the errorbar function(http://matplotlib.org/1.2.1/examples/pylab_examples/errorbar_demo.html)
• R, GNUplot, Octave, Libreoffice calc...
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Materials on the internet
• Confidence calculations:omikron.eit.lth.se/ETSN01/ETSN012013/Material_files/confidence.pdf
• Omnet++ tutorials and documentation:http://www.omnetpp.org/documentation
• MiXiM: http://mixim.sourceforge.net/• Some simple MAC schemes in MiXiM:
http://home.hib.no/ansatte/aaks/omnet.html
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Tutorials organization
• Tutorials are given to prepare you to the exam.• Since time is limited, it is highly advised that you:
• first try to solve the exercises at home,• then have a look at the provided solutions,• and, finally, ask questions during the exercises
sessions.
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Tutorials contents
1.Week1:1.Labs overview (this one)
2.Week2:1.(Tue) Probability review2.(Fri) Reservation schemes
3.Week3:1.(Tue) Reservation schemes2.(Fri) Queuing theory
4.Week 4:1.(Tue) Queuing theory2.(Fri) Link layer
5.Week5:1.(Tue) Link layer2.(Fri) TCP and congestion control
6.Week6:1.(Tue) TCP and congestion control
2.(Fri) Additional exercises7.Week7:
1.(Tue) Additional exercises2.(Fri) Additional exercises
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