Francis H. Shajin

Work place: Department of Electronics and Communication Engineering, Anna University, Chennai, India

E-mail: shajin.mt@gmail.com

Website:

Research Interests: Soft Computing, Image Processing, Machine Learning

Biography

Francis H Shajin graduated from Anna University, India. He has more than 10 years of experience in research and development field. He has published more than 35 papers in international journals. His current research interests include very-large-scale integration, soft computing, image processing, machine learning and networking.

Author Articles
Auto-metric Graph Neural Network based Blockchain Technology for Secured Dynamic Optimal Routing in MANET

By Francis H. Shajin Muthusamy Palaniappan P. Rajesh

DOI: https://doi.org/10.5815/ijcnis.2024.01.10, Pub. Date: 8 Feb. 2024

Mobile ad hoc network (MANET) routing is a generous tactic used for allocating packets to the base station (BS). During the operations of routing, occurrence of malicious node embellishes the mobile ad hoc network operations. For that reason, a trusted distributed routing protocol is obliged that maintains the routing buttressing and the proficiency of mobile ad hoc network. To overcome these challenging issues, Auto-Metric Graph Neural Network based Blockchain technology is proposed in this manuscript for Secured Dynamic Optimal Routing in MANET (BC-SDOR-MANET-AGNN). The proposed approach is simulated in NS-2 tool. The proposed BC-SDOR-MANET-AGNN approach attains 76.26%, 65.57%, 42.9% minimal delay during 25% malicious routing environment, 73.06%, 63.82%, 38.84% less delay during 50% malicious routing environment when analyzed to the existing models, like enhanced hybrid secure multipath routing protocol for MANET (BC-SDOR-MANET-GAHC), an improved ad hoc on-demand distance vector routing security approach based on BC technology in MANET (BC-SDOR-MANET-AODV-MQS) and block chain-based better approach for the mobile ad-hoc networking protocol using ensemble algorithm (BC-SDOR-MANET-E-BATMAN) methods.

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