EKMT-k-Means Clustering Algorithmic Solution for Low Energy Consumption for Wireless Sensor Networks Based on Minimum Me
EKMT-k-means clustering algorithmic solution is one of the well known methods among all the partition based algorithms to partition a data set into group of patterns. This paper presents an energy efficient k-means clustering algorithm named EKMT which is
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Abstract EKMT-k-means clustering algorithmic solution is one of the well known methods among all the partition based algorithms to partition a data set into group of patterns. This paper presents an energy efficient k-means clustering algorithm named EKMT which is based on concept of finding the cluster head minimizing the sum of squared distances between the closest cluster centers and member nodes and also considers the minimum distance between cluster heads and base station. In the proposed protocol the effort was made to improve the energy efficiency of the protocol by re-selecting the cluster head among the most possible cluster heads on the basis of the least distance between new selected cluster head and the base station thus improves throughput and delay. Keywords Wireless sensor networks Cluster centroid Residual energy
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1 Introduction In a Wireless sensor network, a huge number of sensor nodes are deployed in the monitored area and the monitored data is collected by external base station. In the network when battery of node dies a node is no longer useful. This is the reason
B. Jain (✉) DAV Institute of Engineering and Technology, Jalandhar, India e-mail: [email protected] G. Brar BBSBEC, Fatehgarh Sahib, India e-mail: [email protected] J. Malhotra Guru Nanak Dev University, Jalandhar, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2018 G.M. Perez et al. (eds.), Networking Communication and Data Knowledge Engineering, Lecture Notes on Data Engineering and Communications Technologies 3, https://doi.org/10.1007/978-981-10-4585-1_10
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why researchers are now days developing new routing algorithms for wireless sensor networks to save energy and improve QoS parameters like delay, throughput and jitter. Heinzelman et al. [1] developed a hierarchical adaptive clustering routing protocol LEACH to improve energy efficiency and reliable transmission in WSN. New clustering routing algorithms provides energy efficient approaches in data redundancy by reducing the communication distance for wireless sensor networks by data aggregation [2]. In LEACH the run time of network is broken into several rounds by dividing the sensor nodes in the network into several clusters. In this paper, we are introducing an improvement in the algorithms for routing to control traffic and manage energy consumptions. There are various algorithms available for routing. Another efficient method for conserving the energy of sensor networks is data gathering. To remove the redundant data and save the transmission energy is the main purpose of data gathering [3, 4]. LEACH protocol leads to non uniform energy consumption in the network In earlier leach based protocol, cluster head selection criteria is not considering the distance between base station and nearest cluster head having minimum energy [5]. The proposed protocol called EKMT-K means will optimize the energy of the WSN and increase the sensor lifetime as compared to earlier k-means protocols available.
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