Page 168 - 2023-Vol19-Issue2

164 | Al-Jabry & Al-Asadi

energy consumption. Table (I) displays the simulation settings In this study, we compare the efficacy of our proposed
utilized for this investigation. DDCP routing algorithm to that of conventional routing pro-
tocols such as AODV using these performance metrics. The
TABLE I. results demonstrate that the proposed DDCP routing algo-
SIMULATION PARAMETERS FOR EXPREIMENTS rithm outperforms the conventional routing protocol in terms
1, 2 AND 3 of PDR, end-to-end delay, and energy efficiency, proving the
scheme’s efficacy.
Simulation Parameters Value
Number of nodes 1 -500 V. EXPERIMENTAL RESULTS
Packet size 1024 bytes
Simulation time 200 seconds A. Experimental setup
Traffic rate 1 packet/s The NS2-2.35 network simulator was used to test the perfor-
Transmission range 20 meters mance of our suggested DDCP routing method. A popular
CBR traffic 5, 10, 15, 20, 25 tool for modeling wireless sensor networks, NS2 offers a com-
Network size 100 x 100m plete framework for carrying out simulations. It randomly
Packet rate 54 Mbps distributed a network of 30 wireless multimedia sensor nodes
over a 100 m x 100 m area for the simulation. The nodes
B. Performance metrics were powered by 3.7V, 2500 mAh lithium-ion batteries and
Several performance metrics, including packet delivery rate had IEEE 802.11b/g/n wireless transceivers. The transmission
(PDR), end-to-end delay, and energy efficiency, were em- size was set to 1024 bytes, and the simulation ran for 200 sec-
ployed to assess the efficacy of our proposed DDCP routing onds. In terms of end-to-end latency, energy efficiency, and
algorithm. Packet Delivery Ratio: The PDR is the proportion packet delivery rate, we evaluated the performance of the sug-
of packets distributed by the destination node to those sent by gested DDCP routing approach with that of three conventional
the source node. It serves as one of the most crucial indicators routing protocols, including OLSR, AODV, and DSR.
for assessing the effectiveness of routing algorithms. The
PDR is calculated as follows and it is measured in percentage Additionally, the influence of dynamic cooperative range
(%): settings on the performance of the DDCP routing approach
was evaluated, and the best range for enhancing packet de-
PDR = Recieved packetsatdestination × 100% (1) pendability was found. The nodes were prepared with XBee
Packetssendbysource Series 2 wireless modules to verify the suggested strategy in
a practical setting. The obtained findings demonstrated the ef-
End-to-End Delay: End-to-End Delay or E2E latency fectiveness of the proposed plan by showing that the suggested
is the amount of time it takes for a packet to go from its DDCP routing approach outperformed the conventional rout-
source node to its destination node and it is represented in ing protocols, such as OLSR, AODV, and DSR, in terms of
milliseconds (ms). Because it has an immediate effect on the energy efficiency, packet delivery rate, and end-to-end latency.
network’s QoS, this is a crucial indicator for assessing the
performance of the routing algorithm. The End-to-end delay Here, we investigated the performance of four routing
is calculated as follows: protocols - DDCP, OLSR, AODV, and DSR, under similar
simulation settings in order to associate the suggested DDCP
PDR = E2ElatencyorEnd - to - EndDelay routing approach with established routing protocols. The goal
is to produce meaningful insights while comparing the effi-
= Timetaken f orapackettoreachdestination - ciency of the recommended DDCP routing approach against
traditional routing protocols objectively.
T ime packet wassent bysource (2)
The goal of this study is to show that the recommended
Energy Efficiency: Energy efficiency is the quantity of DDCP routing approach overcomes conventional routing pro-
data transferred per unit of energy consumed. It is a cru- tocols in terms of energy efficiency, packet delivery rate, and
cial metric for assessing the efficacy of routing algorithms in end-to-end latency. The comparison study will offer insight-
terms of energy consumption, as it has a direct impact on the ful information and allow us to confirm the efficiency of the
network’s lifespan. Energy efficiency is calculated as: suggested DDCP algorithm.

EnergyE f f iciency = Amounto f datatransmitted (3) B. Simulation Results
In this section, we evaluate the efficacy of the proposed DDCP
E nergyconsumed routing algorithm using simulation results. Using NS2 sim-
ulation software and a testbed with 50 wireless multimedia