Cross-Layer Protocol for WSN-Assisted IoT Smart Farming Applications Using Nature Inspired Algorithm

The Internet of Things (IoT) is a subclass of the Industry 4.0 standard. The functionality of IoT depends on the Wireless Sensor Networks (WSNs) design. The IoT-empowered WSNs received the researcher's attention for the Smart Farming (SF) applications. SF nowadays is required to enhance farm productivity while minimizing the cost and resources. The agriculture sensors devices disposed over the farm collect the on-field farm data and transfer it wirelessly to the base station for decision-making and agriculture monitoring. As the nodes are resource restrained, the process of periodic farm data gathering and multi-hop delivery needs to be effective in terms of Quality of Service (QoS) and energy-efficiency of information transmission by reflecting the long-distance transmission difficulties of SF applications. To enhance the network lifetime substantially of densely deployed WSN for periodically monitoring of farm conditions, we propose a novel Nature-Inspired algorithm-based Cross-layer Clustering (NICC) protocol. We design NICC to find a reasonably better solution for clustering and routing in SF applications. NICC explores the idea of a nature-inspired optimization algorithm called Bacterial Foraging Optimization (BFO) with optimal fitness function, which models the trade-off among the energy efficiency and optimal data transmission. We design a BFO algorithm to select the optimal sensor node for clustering and routing problems based on cross-layer parameters-based fitness value computation. The cross-layer parameter includes the sensor parameters from layers like network layer, physical layer, and Medium Access Control (MAC). The numerical results show the superiority of the NICC protocol for various WSN-assisted SF scenarios against state-of-art clustering techniques.