An energy balanced and nodes aware routing protocol for energy harvesting wireless sensor networks

• Main Authors: Mansura, A., Drieberg, M., Aziz, A.A., Bassoo, V., Sarang, S.
• Format: Article
• Published: Springer 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123490530&doi=10.1007%2fs12083-022-01292-w&partnerID=40&md5=26f38d34cd3fa660ff5b62b5440cedd9; http://eprints.utp.edu.my/28992/
• Institution: Universiti Teknologi Petronas

The lifetime of Wireless Sensor Networks (WSN) is a significant constraint since they are powered by non-rechargeable batteries with limited capacity. A promising solution to the energy issue is energy harvesting (EH). One of the most popular hierarchical routing protocols (RP) is the low-energy adaptive clustering hierarchy (LEACH). Most of the available RPs based on LEACH for EH-WSNs have employed the traditional cluster head (CH) selection based on taking turns, which is unsuitable. Moreover, most of them have not considered the remaining energy and harvested energy, nor investigated the weightages of these energies in selecting the CH. This work proposes the energy balanced and nodes aware (EBNA) routing protocol for EH-WSNs. It considers both the remaining energy and harvested energy along with the number of active nodes in selecting the CH which improves throughput. In addition, the weightages of the energies are investigated. EBNA is evaluated using the network simulator, GreenCastalia in OMNET. It uses the actual solar irradiance data with a resolution of 1 s. The performance is compared with energy-aware distributed clustering (EADC) and clustering routing algorithm of self-energized (CRAS) for EH-WSNs. The results show that EBNA outperforms EADC and CRAS in throughput by up to 58 and 113 and by number of CHs by up to 148 and 541, respectively, during the high irradiance scenarios. In the low irradiance scenario, the improvement in throughput is up to 52 and 98, and the number of CHs is up to 146 and 569, as compared to EADC and CRAS, respectively. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.