It sets up and controls the simulation experiments, moving nodes with the help of the TraCIMobility module.
Under the same number of moving nodes, with the number of nodes increasing (from 100 to 250), the average roses on energy consumption are 115.2, 109.4, 62.3, 85.5, and 62.5 %, respectively.
2. Nodes mobility - by varying the speed of the moving nodes with values 1 m/s, 3 m/s and 5 m/s, (refer Figure 4, 5 and 6). Figure 4 Packet Delivery Ratio at Varying Speed. Figure 5 Average End to End Delay at Varying Speed. Figure 6 Routing Delay at Varying Speed.
In Algorithm 3, for the same number of moving nodes, with the number of nodes increasing, the average roses on energy consumption rise 6.8, 11.6, 7.1, 6.8, and 1.8 %, the range is less than those of Algorithms 1 and 2. Therefore, the saving energy scheme in Algorithm 3 not only saves more energy, but ensures that each node has similar energy consumption, improving network performance.
If this inequality is never satisfied, the node enters the lowest layer M. Getting nodes to choose their layers dynamically in this way moves nodes with a lot of energy into higher layers, where they will work harder, while nodes that are nearly exhausted go to lower layers, where they can conserve energy.
However, the moving node feature is difficult to integrate with the accumulation of a three-dimensional (3D) subsurface stratigraphy, because it requires 3D subsurface interpolation, which results in stratigraphic data loss due to heterogeneity of the subsurface and averaging effects.
In the present article, we attempt to analyze DWOs in several boiling channels with varying lengths (Froude number) adopting moving node scheme (MNS) and fixed node scheme (FNS).
The problem increases when dealing with moving nodes and cluttered indoor environments.
This study provides the research community with an analytical framework which can improve the understanding and use of the RWP mobility model used in the majority of simulation studies with moving nodes.
