Computer Vision Conference (CVC) 2026
21-22 May 2026
Publication Links
IJACSA
Special Issues
Computer Vision Conference (CVC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 17 Issue 1, 2026.
Abstract: Nanotechnology offers transformative capabilities across healthcare, environmental monitoring, and industrial automation. When integrated with modern communication technologies, Wireless Nano Sensor Networks (WNSNs) form the Internet of Nano Things (IoNT), interconnecting nanoscale devices with conventional networks. Despite its potential, efficient routing in IoNT remains challenging due to severe energy constraints, limited processing, and high propagation losses in the terahertz (THz) band. This paper proposes the Distributed Energy-Efficient Protocol (DEEP), a lightweight routing scheme designed for IoNT-based WNSNs. DEEP balances simplicity, connectivity, and sustainability through adaptive retransmission control and a hybrid energy model combining environmental energy harvesting with wireless power transfer. Performance evaluation using the Nano-Sim module of the NS-3 simulator demonstrates that DEEP significantly extends network lifetime, reduces overall energy consumption, and maintains scalability and robust delivery performance with minimal communication overhead.
Saoucene Mahfoudh and Areej Omar Balghusoon. “DEEP: A Distributed Energy Efficient Routing Protocol for Internet of Nano-Things”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.1 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170196
@article{Mahfoudh2026,
title = {DEEP: A Distributed Energy Efficient Routing Protocol for Internet of Nano-Things},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170196},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170196},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {1},
author = {Saoucene Mahfoudh and Areej Omar Balghusoon}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.