Shortest Path Discovery for Area Coverage (SPDAC) Using Prediction-Based Clustering in WSN C. N. Abhilash, S. H. Manjula, R. Tanuja, and K. R. Venugopal Abstract Area coverage has been one among the major limitations in wireless sensor networks (WSNs). The main drawback in WSN is their limited lifetime. Hence, this has become the popular topic in WSNs recent research trend. Optimization of area traversed paths is one of the key factors in the proposal of area coverage approaches in WSN. This work presents the shortest path discovery for area coverage (SPDAC) approach to optimize the path trajectory of mobile relay node (MRN) to solve area coverage problems through the strategic deployment of sensors. Also, we extend the algorithm to reduce static node communication overhead by introducing a new scheme prediction-based clustering protocol for energy consumption (PCP- EC). These two approaches together will help in extending lifetime of the network. Simulations are carried out using network simulator tool to analyze the reduction in number of static nodes interactions and other quality of services. Keywords Area coverage · Energy consumption · Prediction clustering 1 Introduction In WSNs, data collection detected by the nodes that are organized in the area of sensing is one among the most important tasks [1]. Typically, this collection of data mainly relies on wireless transmission between the sink node and sensor nodes that suffer from different situations. For example, wireless communications that C. N. Abhilash (B ) · S. H. Manjula · R. Tanuja · K. R. Venugopal Department of Computer Science and Engineering, UVCE Bangalore University, Bengaluru, Karnataka, India e-mail: abhilashcn83@gmail.com S. H. Manjula e-mail: shmanjula@gmail.com R. Tanuja e-mail: r_tanuja@yahoo.com K. R. Venugopal e-mail: venugopalkr@gmail.com © Springer Nature Singapore Pte Ltd. 2021 N. N. Chiplunkar and T. Fukao (eds.), Advances in Artificial Intelligence and Data Engineering, Advances in Intelligent Systems and Computing 1133, https://doi.org/10.1007/978-981-15-3514-7_101 1345