## 7 Results and Discussion
Effect of Payload: To examine the effect of data payload on network performance, we carried out a series of simulations with data payloads of 200, 300, 400, and 500 bytes. The results from these simulations are shown in Figure 6 and explained in the paragraphs below. Figure 6a illustrates the end-to-end delay as payload (200 bytes to 500 bytes) and node density varied. The graph indicates a significant drop in end-to-end delay as the node density increases, which is because of improved network connectivity at higher node densities. The nodes having more neighboring nodes in their transmission range reduce the number of hops required for data transmission. Fewer hops lead to lower overall transmission delays. Larger payload sizes take more time to transmit due to the increased  
Figure 6: Impact of payload on (**a**) end-to-end delay, (**b**) average energy consumption, (**c**) total energy consumption, (**d**) packet delivery ratio, (**e**) network throughput, and (**f**) dead nodes. data volume, resulting in slightly higher delays. However, in denser networks, the negative impact of larger payload size is mitigated by the availability of more efficient routes, which compensates for the longer transmission delays. This highlights that higher node densities not only reduce delay but also make the network more robust to the challenges posed by larger data packets. Consequently, the network maintains lower delays even with heavier data traffic, optimizing the overall performance. Figure 6b illustrates the average energy expenditure per node as the payload (200 bytes to 500 bytes) and node density varied. The mean energy expenditure decreases as node density increases, which can be explained by the shorter communication paths available in denser networks. With more nodes in the network, data packets require fewer hops to reach their destination, reducing the energy expended by each node during transmission. Smaller payloads such as 200 bytes consume less energy, since they require less transmission time. Larger payloads such as 500 bytes, while consuming more energy initially due to their size, benefit from the efficiency of higher node densities, which compensates for the additional energy costs. The decrease in energy consumption is more obvious due to densely populated regions as the availability of alternative routes helps avoid energy-intensive long-distance transmissions. Figure 6c illustrates the total energy expenditure as the payload and node density varied. The total energy consumption graph reflects a downward trend as node density increases, like the average energy consumption. A larger payload size such as 500 bytes results in higher total energy consumption. However, as the node density increases, the efficiency of the network improves due to a shorter communication path, leading to a decrease in total energy consumption. Denser networks reduce void regions where nodes would waste energy searching for available routes. Figure 6d illustrates the packet delivery ratio as the payload and node density varied. The packet delivery ratio increases rapidly as the node density rises. This is because the higher node density provides more robust connectivity and different paths for data transmission, which helps mitigate the effects of packet loss due to void regions. Also, with larger payloads like 500 bytes, which could increase the chance of packet loss due to longer transmission times, the packet delivery ratio remains high in dense networks. The graph highlights that network density plays a more critical role in ensuring reliable data transmission than payload size, as a dense network can handle lager data volumes without compromising packet delivery. Figure 6e illustrates the network throughput as the payload and node density varied. The network throughput improves as node density increases with larger payload sizes, such as 500 bytes, consistently achieving higher network throughput compared to smaller payload sizes.