Optimized and Dynamic Selection of Cluster Head Using Energy Efficient Routing Protocol in WSN
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Optimized and Dynamic Selection of Cluster Head Using Energy Efficient Routing Protocol in WSN M. B. Shyjith1 · C. P. Maheswaran1 · V. K. Reshma2
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Wireless Sensor Networks plays an outstanding role in providing dynamic cluster head (CH) selection. However, the selection of CH is a major challenge due to erroneous CH selection and can lead to unbalanced energy consumption. This paper addresses this challenge by proposing a hybrid optimization algorithm for CH selection. The proposed CH selection comprises three phases, which includes the setup phase, transmission phase, and measurement phase. At first, the energy and the node’s mobility in the network are initialized. The setup phase is processed by choosing CH using the Optimized Sleep-awake Energy-Efficient Distributed clustering, which is designed by determining the optimal threshold and CH using proposed Rider-Cat Swarm Optimization (RCSO) algorithm. The proposed RCSO is designed by integrating Rider Optimization Algorithm into Cat Swarm Optimization. Here, the threshold and CH are chosen using multi-objective constraints, which involves distance, energy, and delay. After determining the CHs, the data transmission begins from CHs to the base station. At last, in the measurement phase, the residual energies produced from the nodes are being updated. The proposed RCSO method shows superior performance by providing maximal energy, throughput, and the number of alive nodes with values 0.0351 J, 74.715%, and 18 respectively. Keywords WSN · Energy · Mobility · Threshold · Optimizations
1 Introduction The advancements in WSN has gained immense attention in the real-time applications, which involves examining environmental conditions, handling traffic, video surveillance, preventing disasters, monitoring health, medical diagnosis, monitoring climate and weather, monitoring industries, and enterprises [1, 2]. WSN contains different sensor nodes (SN’s), which are deployed randomly for sensing and monitoring the environmental * M. B. Shyjith [email protected] 1
Department of CSE, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu 629 180, India
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Department of CSE, Jawaharlal College of Engineering & Technology, Palakkad, Kerala 679 301, India
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and physical factors. WSN has become a reality as the enhancements and development in sensors and provides petite SN size, containing components related to wireless communication [2]. WSN is responsible for gathering related-data in which the users entails significant information for sensing the SN. WSN are commonly subjected to failures due to energy exhaustion, defects in nodes’ hardware or software, environmental factors, and antagonistic attacks. Thus, it is important to certify a WSN, is accessible throughout the existence of faults or when disruption is detected [4]. For attaining the energy-efficiency and scalability using WSN, clustering is described, which is responsible for
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