Enhanced DV-Hop Algorithm using modified mutation factor based Differential Evolution

Abstract

The Internet of Things (IoT) becoming popular day by day as it's a vast set of applications. All these applications are based on smart and tiny sensors. In many applications, information sensed by the sensor is useful, if its location is known. Therefore, the sensor node's accurate location is required in the monitoring region for realistic applications. In, a Wireless Sensor Network (WSN), finding the correct location of sensors is a challenging task. To overcome the shortcoming of DV-Hop, in this paper, modified differential evolution-based enhanced DV-Hop (DEEDV-Hop) is proposed. The proposed DEEDV-Hop has three phases, phase one is similar to the original “DV-Hop”, in the second phase, the hopsize of Beacon Nodes (BN) is calculated at Unidentified Node (UN) to reduce the energy consumption and at least three BNs is selected in the nearby vicinity of UN. For hopsize computation, only those BNs are selected which have their mutual hop distance close to the integer value of communication radius (R). Finally, the modified differential evolution (DE) algorithm is used to find the location of UNs. The adjustment factor is added to refine the hopsize. The simulation findings confirm that, when compared to existing localization schemes, our proposed technique enhances Localization Accuracy (LA) and minimizes Localization Error (LE), Localization Error Variance (LEV).