BRMFC: Design of a Bioinspired Routing Model with Fan Clustering for Wireless Sensor Networks
Keywords:
Wireless, Sensor, Network, Routing, Bioinspired, Fan, Shaped, ClustersAbstract
Wireless Sensor Networks (WSNs) are in constant need of power conservation, and as a result, a broad variety of protocols are recommended for low power clustering and routing activities. This is owing to the fact that WSNs need to save as much power as possible. However, the majority of these protocols have a higher level of complexity and a lower level of energy efficiency, both of which restrict their ability to scale to bigger networks. To overcome this drawback, a Bioinspired Routing Model with Fan Clustering for Wireless Sensor Networks is discussed in this text. The proposed model initially performs destination-aware Fan Shaped Clustering (FSC) and groups nodes based on their distance measures. These FSCs are further processed via use of a bioinspired model that uses Genetic Algorithm (GA) for selection of optimum routing nodes. These nodes are selected based on their residual energy & distance metrics. The model uses a light weight fitness function that assists in faster solution convergence, with better routing paths. It was evaluated on systems with small, medium, and large scales, and its Quality of Service (QoS) metrics were compared to those of other models that are considered to be state-of-the-art. The results of this comparison showed that the model that was suggested was capable of reducing power consumption by 5.9%, reducing delay by 8.5%, increasing PDR by 2.5%, and increasing throughput by 10.5%. As a result, it is extremely valuable for deploying real-time networks.
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