Abstract
Background: Most existing works on Wireless Sensor Networks (WSNs) assume node deployment in regular terrain. Most of the works have considered the fact that in most real-life applications, nodes are actually in irregular terrain but are analyzed in two-dimensional plane. This paper attempts to analyze a sensor network in three-dimensional plane. The energy conservation and network lifetime prolongation problem along with secondary constraints of the sensor network are rigorously examined.
Method: Through the investigation of existing works, it is found that a more practical way to analyze monitoring of real-life applications of WSNs is deployment of sensor network in irregular terrains e.g. mountainous regions. This paper designs a random node deployment scheme with the use of two ray radio propagation model for transmitting information through the channel. The communication coverage of the sensor nodes is defined by a probabilistic sensing model as deterministic sensing models are more effective with regular terrains than the irregular terrains.
Results: Aimed at making progress on the constraints like energy conservation and lifetime prolongation, ML-MAC scheme is used for the analysis of a randomly deployed network. Results indicate an improvement of 21.98% in network lifetime and 1.25% in received throughput in irregular terrains when compared with regular terrains.
Conclusion: This paper compares two scenarios with same parameters but different architecture i.e. regular and irregular. The impact of various performance parameters like network lifetime, number of packets dropped, average jitter and average throughput on performance of regular and irregular terrain networks is evaluated. Although a sensor network is considered as a regular terrain network ideally, but a lot of real life scenarios actually are irregular terrains. The use of ML-MAC protocol improved the performance of both regular and irregular networks.
Keywords: Wireless Sensor Networks (WSNs), ML-MAC, Regular Terrain, Irregular Terrain, QualNet 6.1 Simulator, nodes.
Graphical Abstract