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GTFT node’s behaviour optimization experiments (shown in
Table I) have four control parameters (which represents the
four factors that are mentioned above), where each parameter
has three levels (values), so, L9 orthogonal array is selected.
The parameters are:
• F1: Power constraints per node (P). Where (L1= 1,
L2=0.5, L3=0.2).
• F2: Number of packets required to forward (N). Where
(L1=1000, L2=500, L3=200).
• F3: power consumption per node (C). Where (L1=0.001,
L2=0.0008, L3=0.0003).
• F4: Grade of generosity GoG (e). Where (L1=0.08,
L2=0.05, L3=0.02).
When the OA has designated the iterations or trials, experi-
ments can be done. The trial number is concluded based on
the application budget and the complication of experiments.
For the GTFT node’s behaviour experiments, it may contain 3
trials, and at finally, each trial has three outcome values which of 200 packets, which means that all packets were redirected.
are:
• T1: is the measured Throughput.
• T2: is the measured ?.
• T3: is the measured ? .
Then, SNR is calculated using (2), (3), (4), (5), and (6). All
of experiments’ calculations are shown in Table II. After
that, the average SNR value per parameter is calculated in
accordance with given levels. The calculations for the ? (F1),
N (F2), c (F3), and e (F3) are shown in Table III. From the
DOE of GTFT node behavior, notices that Taguchi Method
is perfect for identifying the best impact factor on the node
behavior from the four given factors. Table IV concluded the
results. Since this article’s objective is to present the problem
of improving GTFT node behaviour as a series of experiment
design tests, Taguchi’s method of designing experiments has
been used. The strength of using the Taguchi method in this
article is measuring design quality using the signal-to-noise
ratio (SNR) and the orthogonal array principle that is used to
study the influence of several design parameters: number of
packets (N), power consumption (c), power constraint of the
node (?), and GoG, respectively. The Taguchi method is a
robust design approach that uses many insights from statistical
experimental design to evaluate and implement process im-
provements. The basic principle is to improve product quality
by reducing the impact of the causes of the difference without
eliminating the causes.
It should be mentioned that the Taguchi DOE was generated
for the L9 OA using Minitab version 20. Using MATLAB
Jumaa, Mohamad, Allawy & Mohammed
2018, the simulation of the ad-hoc network was performed.
The information regarding the parameters of ad-hoc networks
was gathered using MATLAB and subsequently imported into
the Minitab DOE in preparation for Taguchi analysis.
VII. GTFT NODE BEHAVIOUR RESULTS
Impact factor levels are taken as initial parameters and en-
tered GTFT according to the OA-designed experiments of the
Taguchi method which are used to evaluate node behaviour
performance. Fig. 1 to 9 show the performance of the node.
Based on Taguchi optimization, statistics show that the op-
timal case for a node to behave as a relay is in the third
experiment where the values of ? and ? were one due to the
availability of ideal factors that are: the power of the node at
the highest level, that is, the battery node is fully charged, the
number of packets at its lowest level where it is equal to 200,
and the packets that are required to be redirected by the node
consume energy at the lowest level (0.0003 watts), that it is
mean, the two hundred packets consume 6% of the node’s
battery power.
The throughput was as high as possible, and it was 200 out
The influencing factor mainly is the number of packets re-
quired to be redirected, accordingly, the level of generosity
does not effectively affect the behaviour, of the node because
in the third experiment, the level of generosity was at the
lowest level, which is 0.02. While most selfish behaviour of
the node was in experiment 8 where the throughput equal to
41 out of 500 packets due to the non-ideal conditions of the
node:
• The power of the node is at the lowest level. It is equal
to 0.2, meaning that the battery is almost empty and at
the level of 20% of the remaining charge, which drives
it to selfish behaviour to maintain the level of its ability
to stay alive (power on).
• The number of packets was at a high level, equal to 500.
The packets that are required to be forwarded by the node con-
sume power at the highest level of 0.001 watts, meaning that
the 500 packets consume 50% of the energy of the full node
battery, in other words, that the node battery is not sufficient
to redirect the packets. The selfish behaviour of experiment 8
was at the same level of generosity as that of the ideal cooper-
ative behaviour of experiment 3, equal to 0.02.
Fig. 1 shows the behaviour of a node for experiment number
(1), and from our observation of the shape, when ordering
more than 200 packets, the ? of the node begins to decrease
dramatically to reach a value of zero when requesting more
than 1000 packets. From Fig. 2 and at experiment number
(2), we notice that the node behaves roughly like experiment