Title: Transmission power minimisation in nano biosensors for largescale flow-guided intra-body communication

Authors: B. Gopi; R. Vasanthi; G. Sugitha; B.C. Preethi

Addresses: Department of Biomedical Engineering, Sona College of Technology (Autonomous), Salem – 636005, Tamil Nadu, India ' Department of Computer Science and Engineering, R P Sarathy Institute of Technology (Autonomous), Salem – 636305, Tamil Nadu, India ' Department of Computer Science and Engineering, Muthayammal Engineering College (Autonomous), Rasipuram – 637408, Tamil Nadu, India ' Department of Electronics and Communication Engineering, St. Xavier's Catholic College of Engineering (Autonomous), Chunkankadai – 629003, Tamil Nadu, India

Abstract: The nano biosensors are designed to detect and analyse biological molecules or substances that operate collectively and have to achieve precise functioning of sensing or actuating. However, their routing effectiveness is impacted by factors such as energy consumption, bit error rate, and transmission power. Hence, we have proposed a flow-guided nanonetwork model, incorporating the symbol-level precoding technique to enhance power optimisation. We have also proposed an improvised artificial protozoa optimisation algorithm to improve scalability in mobile nano biosensors, reduce communication overhead, and optimise energy consumption. The integration of the SLP technique effectively reduced transmission power for nano-nodes, significantly enhancing the reliability and accuracy of the proposed model. Performance evaluations focused on metrics such as transmission power, end-to-end delay, packet delivery ratio, bit error rate, energy consumption, network lifetime, scalability, communication overhead, and network throughput. Simulation results conclusively demonstrated the exemplary performance of the proposed model compared to other network models.

Keywords: artificial protozoa optimisation; APO; bit error rate; BER; flow-guided nanonetwork; intra-body network; nano biosensor; symbol-level precoding.

DOI: 10.1504/IJSNET.2025.146142

International Journal of Sensor Networks, 2025 Vol.48 No.1, pp.1 - 12

Received: 17 Jul 2024
Accepted: 10 Feb 2025
Published online: 07 May 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article