Class Topper Optimization Based Improved Localization Algorithm in Wireless Sensor Network

Wireless Senser Network (WSN) is broadly employed in many real life applications. WSN can be applied for sensing, collecting, processing and transmission of information. The importance of optimization methods plays a key role in the consistent and realistic estimation of the position of the sensor node. This article presents for improved DV-Hop localization using Class Topper Optimization (CTO) to address the current drawback of conventional DV-Hop. In the proposed algorithm, a factor to modify the hop size of the beacon nodes is presented. It is concluded from experimental assessment that the proposed optimized algorithm plays better than alternative algorithms with similar characteristics under the influence of variable number of nodes, beacon nodes and range. The proposed algorithm is compared with conventional DV-Hop, IDV-Hop algorithm and DV-Hop-based particle swarm optimization. Simulation results show that the localization error, error variance and accuracy are minimized by the proposed localization algorithm relative to current localization techniques.