Region Based Cluster Aided Routing Protocol for Environment Monitoring in Heterogeneous Wireless Sensor Networks

Authors

  • Saritha Mahankali Department of Computer Science & Engineering, Saveetha School of Engineering, SIMATS, Chennai, India
  • R. Kesavan Department of Computer Science & Engineering, Saveetha School of Engineering, SIMATS, Chennai, India
  • S A Kalaiselvan Department of Artificial Intelligence and Machine Learning, Rajalakshmi Engineering College, Chennai, India

DOI:

https://doi.org/10.37934/araset.47.1.180198

Keywords:

Heterogeneous wireless sensor networks, Routing protocols, Heterogeneity, Region based clustering, Stability period

Abstract

Heterogeneous wireless sensing networks (HWSNs) that are limited by their batteries' power consumption might benefit greatly from more efficient routing algorithms. It is essential that routing accounts for the diversity of network nodes to achieve optimal performance. This letter considers sensor nodes with random initial energies and random disparities in data output rate (traffic) to build a realistic clustering-based WSN suitable for heterogeneous sensing applications. The protocol divides the space into numerous zones with different distance thresholds to deal with the hotspot problem that the multi-hop method creates. The advantages of region-divided routing ensure that only qualified nodes compete for the role of cluster's head during the choice phase and that the cluster heads with the greatest remaining energy in the extremely energetic area are selected as the relay node throughout the inter-cluster routing that includes several hops phase. The simulation findings demonstrate that the protocol may efficiently equalize energy consumption throughout the network, eliminate the issue of "hot spots," be used in an energy-diverse system, and lengthen the service life of the network.

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Author Biographies

Saritha Mahankali, Department of Computer Science & Engineering, Saveetha School of Engineering, SIMATS, Chennai, India

sarithamahankali786@gmail.com

R. Kesavan, Department of Computer Science & Engineering, Saveetha School of Engineering, SIMATS, Chennai, India

kesavan456@gmail.com

S A Kalaiselvan, Department of Artificial Intelligence and Machine Learning, Rajalakshmi Engineering College, Chennai, India

kalaiselvan678@gmail.com

Published

2024-06-21

Issue

Section

Articles