E2BNAR: Energy Efficient Backup Node Assisted Routing for Wireless Sensor Networks

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Published: Mar 11, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i3s.6181
Keywords:
Energy Harvesting, Backup Nodes, Harvesting Rate, Depletion Rate, Activation Energy, Awaken Sensor Number

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Akshatha Hari Bhat
Vidyalankar Institute of Technology Mumbai, Shri Madhwa Vadiraja Institute of Technology & Management, Udupi, Affiliated to Visvesvaraya Technological University Belagavi
Balachandra Achar H V
Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal

Abstract

In Wireless Sensor Networks (WSNs), each sensor node can only use so much power before recharging. If energy is depleted too quickly, nodes will fail one by one, bringing down the network as a whole. To this end, a design is needed to reduce the burden on the sensor nodes' power supplies while extending the network's useful life. This paper proposes a new approach, called Energy Efficient Backup Node Assisted Routing, to accomplish this (E2BNAR). Each primary node in the network has a group of backup nodes to ensure the network continues functioning. Assuming that the sensor nodes are capable of energy harvesting, E2BNAR finds the best backup node by analyzing the statistical relationship between energy harvesting and consumption rates. Periodically, residual energy is used to analyze the current energy consumption rate. When evaluating performance, several different indicators are taken into account. These include the Packet Delivery Ratio, Throughput, Average Energy Consumption, and Number of Awakened Sensor Nodes. Through analysis and experimentation in several settings, the proposed method's efficacy has been established.

Article Details

How to Cite
Bhat , A. H. ., & H V, B. A. . (2023). E2BNAR: Energy Efficient Backup Node Assisted Routing for Wireless Sensor Networks . International Journal on Recent and Innovation Trends in Computing and Communication, 11(3s), 193–204. https://doi.org/10.17762/ijritcc.v11i3s.6181
Issue
Vol. 11 No. 3s (2023)
Section
Articles

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