Instructions to authors for the preparation of manuscripts

parts of the precast concrete) for the storage probability 
P≥0.3, in 97% of cells for P=0.2, and in 91% of cells for 
P=0.1. 
Fig. 3. Logical division of the precast concrete into pieces of 
2m×2m. 
Fig. 4. Uniformity and quality of data distribution of USEE. 
4.2.2. Storage capacity of the precast concrete 
In this section, we evaluate the storage memory capacity of 
the WSN throughout the precast concrete lifecycle. Figure 5 
shows that USEE reaches 27000 storage process in the WSN 
inside the precast concrete. Using USEE, the WSN could thus 
execute all the 11500 storage process during all the precast 
concrete lifecycle (11500 operations as shown in table 1). 
Fig. 5. Storage capacity of WSN inside the precast concrete using 
USEE. 
4.2.3. Delay of data storage process 
The delay is the time elapsed from the beginning of 
dissemination by the master node to the end of the process by 
all others nodes. This parameter is influenced mainly by the 
message transmission strategy of USEE. The simulation 
results in Castalia show that USEE allows a delay less than 
0.5 second for all the storage probability (min≈0.28s and 
max≈0.39s). As shown in table 1, the delay constraint of data 
storing in the precast concrete must be less than one minute. 

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This shows that compared to our results, it is a low stress 
since the delay is less than 0.5 second. 
4.3. Data retrieval performance 
In the following, RaWPG is evaluated in terms of response 
delivery ratio and the average delay. 
4.3.1. Response delivery ratio 
Figure 6 shows the average delivery ratio of RaWPG. It 
highlights that RaWPG ensures a response delivery ratio 
upper to 90% in the precast concrete. As presented in (Mekki 
et al., 2016c), RaWPG uses a link cost function which allows 
choosing the most powerful node as next hop in the WSN. 
Thus, the request and response messages are forwarded 
through a high quality of service path. 
Fig. 6. Response delivery ratio of RaWPG. 
4.3.2. Delay of data retrieval process 
The delay is the elapsed time between the beginning of 
request transmission and the reception of the response 
message by the master node (i.e. the user). The simulation 
results in Castalia show that RaWPG ensures a delay less 
than 0.9 second for all the path length (min≈0.12s for TTL=1 
and max≈0.81s for TTL=8). As shown in table 1, the delay 
constraint of data reading in the precast concrete must be less 
than 5 second. This shows that compared to our results, it is 
also a low stress since the delay is less than 0.9 second for all 
the path length. 
4.4. WSN lifetime estimation 
In this section, the WSN lifetime inside the precast concrete 
is estimated. The needed energy is estimated for each node to 
“live” all the precast lifecycle (14 years). The energy 
consumption of USEE and RaWPG was measured and 
plotted in figure 7. Figure 7 shows the average energy 
consumption of a node inside the concrete for different 
number of storage and reading operations, respectively 
performed using USEE and RaWPG. Using figure 7, the 
trend line of USEE protocol could be calculated, it gives the 
following equation: 
y
= 0,00943782 
x
+ 0,314038 
(1) 
As shown in table 1, the WSN inside the concrete must 
ensures at least x=11500 storage operations. Through 
equation 1, each node should be empowered with at least 
y=109 Joules of energy capacity to execute this number of 
operations. 
In addition, the trend line of RaWPG protocol gives the 
following equation: 
y
= 0,009864048 
x
(2) 
As shown in table 1, the WSN inside the concrete must also 
ensures at least x=11553 reading operations. Through 
equation 2, each node should be empowered with at least 
y=114 Joules of energy capacity to execute this number of 
operations. 
As conclusion, to execute all the storage and reading 
operations during the precast concrete lifecycle, each node 
must have at least a total energy of 223 Joules (109 Joules + 
114 Joules). By adding the energy required for the sensing 
module and for the sleep mode, the 
SensorCube
node 
(voltage = 2.4 V) must be equipped with battery of 350 mAh 
as shown in table 2, to ensure a WSN lifetime of over 14 
years (this period corresponds to the duration of 
BOL+MOL+EOL of precast concrete). However, battery 
lifetime of WSN is actually limited to few years. As solution, 
an energy scavenging module could be used for continuous 
battery charging. Moreover, many academic and industrial 
researches, such as (Ongaro et al., 2012) (Merla et al., 2016) 
(Zhang at al., 2016), work on increasing the battery lifetime. 
Also, there is an early stage research regarding production of 
sensors node without batteries, using similar technologies 
applied to passive radio frequency identification (RFID) 
chips without batteries (Vujic et al., 2012). In the future, 
WSN technologies could improve the overall duration of 
sensor nodes lifetime and thus it could reach 14 years without 
charging or replacement of its battery. 
Fig. 7. Consumed energy for different number of storage and 
reading process for USEE and RaWPG, respectively. 
Table 2. 
SensorCube
lifetime vs. Battery capacity.