Fractional-Grasshopper Optimization Algorithm for the Sensor Activation Control in Wireless Sensor Networks

The progression in wireless sensor network (WSN) has been increased and gained immense attention in computer vision. In WSN, a large number of sensors are deployed for performing distributed sensing of target field. The conventional methods used wireless chargers for providing the energy to sensor nodes, but the supplied energy is not sufficient for controlling the sensor nodes. Thus, this paper proposes a technique for reducing the energy consumption per node by adapting effective scheduling of sleep/awake of the nodes. The method undergoes two phases for the sensor activation namely, initialization phase, and activation phase. The initialization phase is progressed by the network initiation, which is done to convey the network parameters to the nodes or sensor. Then, in activation phase, the proposed optimization algorithm is utilized for activating the sensors in each slot. The proposed fractional grasshopper optimization algorithm (Fractional-GOA) is the integration of the fractional calculus in grasshopper optimization algorithm (GOA). Thus, the proposed method generates the control regarding the turn-ON or OFF of the sensors, which symbolizes the active sensors and engages itself in sensing and monitoring the distributed environment. The proposed method outperforms other existing method with maximal energy, throughput, and alive nodes of 0.111, 85%, and 11, respectively.