ITS323 Introduction to Data
Communications Assignment
Students: Steven Gordon and Thanaruk Theeramunkong
Group: G00
This is an example report, highlighting what you should include. You may edit this report, changing
the text where necessary. You must delete the comments that I make, which are in yellow italics, like
this one. You may also follow a different style or structure, as long as you at least include the
information given in this example.
1
Experiment Setup
This section should briefly describe or list the setup of your experiments. E.g. your operating
system, computer specification and software used. You may write this as a table, a list or in words.
If you performed your experiments across two or more different computers, then list each one. An
example, in table format, is below.
Host CPU
Intel i5-3570K 3.4GHz
Host RAM
8 GB
Host OS
Ubuntu Linux 14.04 LTS
Virtual Machine
VirtualBox 4.3.10
Virtual Network
virtnet r41
Table 1: Experiment Setup
2
Parameter Values
This section should list the values of parameters used in all experiments. I distinguish between two
types of parameters: fixed parameters have values that you don't change in the experiments (you
always use the same value). Variable parameters have values that you changed in different
experiments. Examples are given in each subsection.
2.1 Fixed Parameters
The first column lists the parameter name, the second column gives the value of the parameter that
you used and the third column is the unit.
Parameter
Downlink data rate
Downlink delay
Number of frames
...
Table 2: Fixed Parameters
Value
Unit
100
Mb/s
0
ms
1000
frames
2.2 Variable Parameters
The first column lists the parameter name. The second column list the range of values that you use
for that parameter. There are different ways to list a range. For example “1 .. 10” means the values
are 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. Whereas “0 : 0.01 : 0.05” means a step of 0.01 was used giving the
values 0, 0.01, 0.02, 0.03, 0.04, 0.05. You may also just list the values in a comma separated list.
The fourth column gives the count of parameter values you used, for example “10” different values
of uplink data rate. The count is useful for getting a quick understanding of the number of
experiments to be performed. In the example below, there are 10 x 10 x 6 x 4 x 2 x 7 = 33600
experiments in total. Of course you probably will not run 33600 experiments. Therefore you should
carefully plan which range of values you will use for each parameter. You may also not perform
every combination. For example, maybe you try all 10 values of uplink data rate when max window
size is 1; but then for different max window size (3, 7, 15) you use just one value of uplink data rate
(say 1 Mb/s). That reduces the total combinations of uplink data rate and max window size to 10 +
3 = 13 (instead of 10 x 4 = 40).
Parameter
Range
Unit
Count
1 .. 10
Mb/s
10
Uplink delay
20 : 20 : 200
ms
10
Frame error rate
0 : 0.01 : 0.05
-
6
1, 3, 7, 15
frames
4
Data size
10000, 20000
Bytes
2
Timeout
0, 0.5 : 0.1 : 1.0
s
7
Uplink data rate
Max window size
...
Table 3: Variable Parameters
3
Performance Metrics
This section should list the values you measure. In this assignment, the only performance metric of
interest is the throughput at the server. Another thing to mention is the number of repetitions of each
experiment you performed. If you ran an example with the same parameter values multiple times
and then took the average of the measured values, then you should mention the number of
repetitions (this may not be relevant for this assignment - you don't have to perform multiple
repetitions, but you may). An example is below.
The performance metric(s) are:
1.
Throughput, in bits per second, as measured at the server
Each experiment was performed 3 times, with the average of the 3 values reported in results.
4
Mathematical Model
This section presents the way you calculated the “expected” results. Remember in the assignment
you must both measure the throughput at the server (using the Python code) and convert it to
efficiency, as well as calculate the expected efficiency. Then when you plot the measured efficiency,
you also plot and compare with the expected efficiency. I recommend you first list the parameters
(give them variable names) and then present one or more equations that you use to calculate
expected efficiency. You should use a similar equation in your spreadsheet to calculate the expected
efficiency. Below is an example (use your equation editor to make them look better than mine). You
may have multiple efficiency equations, e.g. one for stop-and-wait flow control (no errors), another
for sliding-window flow control (no errors), and a third for stop-and-wait error control (with
errors).
The variables use in the mathematical model used to calculate expected efficiency are:

Uplink data rate, ru Mb/s

Downlink data rate, rd Mb/s

Round trip time, RTT s

Frame size, f Bytes

...
Round trip time, RTT, is calculated as:
RTT = du + dd
Expected throughput, ρ, is calculated as:
ρ = ...
Expected efficiency, η, is calculated as:
η = ρ / du
5
Results and Conclusions
This section should present plots of efficiency (both measured and expected) versus different
variable parameter values. For example, there may be a plot of efficiency vs uplink data rate. And
then another plot of efficiency vs frame size. Each plot should have a caption (or title) that makes it
clear what it is showing (e.g. “Efficiency vs frame size”). You may divide this section into multiple
sections, e.g. different sub-sections for stop-and-wait flow control, sluding-window flow control and
stop-and-wait ARQ. After each plot you must summarise the trend(s) you observe and the reason(s).
This may be short - a few sentences. Below is an example plot and description. Of course your plots
will be produced using the spreadsheet data and look much better.
Illustration 1: Stop and Wait Efficiency with Varying Data Size
We observed that with increasing the amount of data sent per frame, the efficiency of stop-and-wait
flow control increased. The increase was much more significant when the data size was within the
range of 100 to 1000 Bytes. This is because ... . The measured efficiency was lower than the
expected efficiency because ... .