consumption is defined as the total amount of energy (computation and communication
power) consumed by all the participant sensor nodes during the simulation time
until the WHD algorithm calculates the total hole area that are found in ROI. Figure
7 shows the simulation results of the average energy consumption by using all the
participant nodes out of the total deployed sensor nodes to calculate the holes
area in the ROI with random number of holes and fixed number of sensor nodes.
As known the energy
consumption is directly proportional to the network density (number of deployed
sensors) in the ROI, so as the number of deployed sensor nodes increases the
average energy consumption increases and vice versa. Since the energy
consumption is mainly caused by communication, WHD uses only a defined number
of sensor nodes, this leads to the minimal communication cost for neighborhood
discovery and control information exchange between sensor nodes and the base
station node. Also the amount of aggregated data by the HNs are the minimal due
to the minimal use of sensor nodes in each cell, so the average energy
consumption decreases accordingly.
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It is clear from
Figure 7 that WHD algorithm outperforms PD algorithm in terms of average energy
consumption by approximately 44% average along the selected number
of sensor nodes, and
outperforms VCDHA by approximately 21% average along the
selected number of sensor nodes. The enhancement of average energy consumption is mainly
due to the participation of less nodes to detect and calculate the holes area,
and reduction of the communication between sensor nodes and base station. While
the WHD algorithm saves more power to calculate the holes area compared to
other protocols, so WHD enhances the network life time and reduces the communication
overhead, this is done mainly due to the reduction of communication between the