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Optimization of Adaptive Resonance Theory Neural Network Using Particle Swarm Optimization Technique Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Classification-Based Clustering Approach with Localized Sensor Nodes in Heterogeneous WSN (CCL)

Authors : Ditipriya Sinha, Ayan Kumar Das, Rina Kumari, Suraj Kumar

Published in: Advances in Machine Learning and Data Science

Publisher: Springer Singapore

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Abstract

In wireless sensor network, random and dense deployment of sensor nodes results in difficulties for sink node to detect the location of them without GPS. The inclusion of GPS for all sensor nodes increases the deployment cost. Energy is another constraint in wireless sensor network during data forwarding. In this paper, the proposed protocol CCL has applied the modified version of DV-hop technique to detect the location of sensor nodes without using GPS. Here, event-based clustering is designed to save the energy of nodes, which is classified using support vector machine. Packet is forwarded to the sink node by greedy forwarding technique. Packet loss is also removed by involving an antivoid approach called twin rolling ball technique. Simulation results show that the performance of CCL is enhanced with compared to LEACH, HEED, EEHC, DV-hop, and advanced DV-hop.

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Metadata
Title
Classification-Based Clustering Approach with Localized Sensor Nodes in Heterogeneous WSN (CCL)
Authors
Ditipriya Sinha
Ayan Kumar Das
Rina Kumari
Suraj Kumar
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Machine Learning and Data Science

Print ISBN: 978-981-10-8568-0

Electronic ISBN: 978-981-10-8569-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-8569-7_32

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