Srinivasulu Boyineni et al., International Journal of Advanced Trends in Computer Science and Engineering, 10(3), May - June 2021, 1543 – 1551 1543 ABSTRACT Wireless sensor networks (WSNs) are widely used in various applications such as defense, forest fire, healthcare, structural health monitoring, etc., because of its flexibility, low cost and tiny. In WSNs, the sensor nodes are scattered over the target area to acquire the data from the environment and transmit it to the base station via single or multi-hop communication. Due to the sensor nodes' constrained battery, the sensor nodes near the base station are more involved in data transmissions. These relay nodes drain more energy and die soon, leading to a hotspot/energy-hole problem. Several algorithms have been proposed in the literature to address the hotspot problem using the mobile sink. However, most of the existing approaches are highly computational and also provide a static solution only. In this context, we proposed an energy-efficient dynamic mobile sink path construction with low computational complexity for data acquisition in WSNs. We use the minimum spanning tree-based clustering for selecting the data collection points and a computational geometry-based method to identify the visiting order of the data collection points by the mobile sink. Our proposed work is better than the existing approaches in terms of average energy consumption, network lifetime, fairness index, buffer utilization, etc. Key words: Wireless Sensor Networks, Mobile sink, Energy-efficient, Minimum Spanning Tree, Clustering. 1. INTRODUCTION Wireless sensor networks (WSNs) are more prevalent in recent years due to its vast applications such as Domotics, forest fire, defense, healthcare, security surveillance etc. The WSNs are also playing a vital role in the Internet of Things (IoT) [1]. In WSNs, a set of sensor nodes (SNs) are scattered to acquire the data and transmit it to the base station (BS) for further analytics. These data transmissions use either single-hop or multi-hop communication mechanisms. Single-hop communications are used when the SNs are in the range of BS. So, in most cases, the data transmission uses multi-hop communications. The battery-equipped SNs consume more energy due to heavy transmissions rather than for processing the data. Significantly, the SNs which are near to the BS consumes more power due to the relay. These heavy consumptions cause hotspots or energy-hole problems in the WSNs. The hotspot or energy-hole problem isolates a part of the WSNs from the BS [2, 3]. A mobile sink (MS) is introduced to gather the data from the sensor nodes by traveling in the network which avoids the data relay between the SNs [4,5]. However, visiting each SN in the network is difficult which delays data collection as well as data loss due to limited buffers. Instead of visiting each SN in the network, the MS visits a set of data collection points called rendezvous points (RPs). All the remaining SNs can send their data to the nearest RPs. The optimal selection of the RPs improves the data collection process by prolonging the network lifetime. However, choosing the best RPs in the WSNs is a challenging task. Because, choosing the large number of RPs, increases the traveling time of the MS and because of its limited number of RPs increases the data relay between the SNs and RPs. Deciding the best RPs in the network is not only a challenging task, but also a trajectory among them. There are several works in the literature to address this challenge, but most of them are static as of my knowledge [6,7]. The secured message delivery-based vehicular communication is presented in [8]. In this context, this paper proposes an Energy-efficient Dynamic Mobile Sink Path planning (EDMSP) algorithm for WSNs which improves the efficiency of the data gathering approach by prolonging the network lifetime. The EDMSP initially select the best set of dynamic RPs using minimum spanning tree (MST)-based clustering. There are several MST-based clustering methods in the literature [9,10], but we perform a novel clustering method in this work according the Energy-efficient Dynamic Mobile Sink Path Planning for Data Acquisition for Wireless Sensor Networks Srinivasulu Boyineni 1 , Dr.K. Kavitha 2 , Dr.Meruva Sreenivasulu 3 1 Research Scholar, Department of CSE, Annamalai University, Chidambaram, India. srinivasulu.inf@gmail.com 2 Associate Professor, Department of CSE, Annamalai University, Chidambaram, India. kavithacseau@gmail.com 3 Professor and Head, Department of CSE, K.S.R.M College of Engineering, Kadapa, Andhra Pradesh, India, mesrinu@rediffmail.com ISSN 2278-3091 Volume 10, No.3, May - June 2021 International Journal of Advanced Trends in Computer Science and Engineering Available Online at http://www.warse.org/IJATCSE/static/pdf/file/ijatcse091032021.pdf https://doi.org/10.30534/ijatcse/2021/091032021