Work place: Department of Networking and Communications, SRM IST, Kattankulathur-603203, Tamil Nadu, India
E-mail: h568karthikeyan@outlook.com
Website:
Research Interests:
Biography
H.Karthikeyan (Karthikeyan Hitler) received B.Tech degree in Information Technology from Vel Hightech Dr RR Dr SR Engineering College, Avadi affiliated to Anna University, Chennai, Tamil Nadu in 2010. M.Tech Degree in CSE from SRM Institute of Science & Technology, Kattankulathur, affiliated to SRM University, Kattankulathur, Tamil Nadu in 2014. Ph.D Degree in CSE from SRM Institute of Science & Technology, Kattankulathur, affiliated to SRM University, Kattankulathur, Tamil Nadu in 2025. He is currently working as an Assistant Professor at the Department of Networking and Communications, SRM Institute of Science & Technology, Kattankulathur, Tamil Nadu, India. His research interests include IoT, ad-hoc networks, and Network Security.
By Sudha Y. Karthikeyan H. Prabha M. Sree Southry S.
DOI: https://doi.org/10.5815/ijcnis.2026.01.04, Pub. Date: 8 Feb. 2026
The global shift from 5G to 6G wireless communication networks presents immense challenges in managing resources for ultra-dense, heterogeneous, and latency-sensitive 6G applications such as holographic communications, autonomous systems, and the Internet of Everything (IoE). Traditional resource allocation methods struggle to meet the dynamic and complex demands of 6G, leading to inefficiencies, higher latency, and fairness issues. To address these challenges, we propose a novel framework called Proof-of-Resource enabled 6G Resource Management Using Quaternion-Attentive Cascaded Capsule Networks (Caps-PoR). Our approach integrates Quaternion-Attentive Cascaded Deep Capsule Networks (Q-AtCapsN) to improve the accuracy of predicting resource demands by capturing real-time multi-dimensional dependencies. Additionally, we optimize resource allocation dynamically through an Enhanced Collaborative Learning Algorithm (ECoLA), which supports decentralized decision-making across multiple nodes, significantly reducing latency. The Proof-of-Resource mechanism ensures transparency, fairness, and trust, preventing resource misallocation while ensuring equal access. Performance evaluations show that Caps-PoR outperforms traditional methods in 6G multi-access edge computing (MEC) scenarios, achieving over 98% resource utilization efficiency, a latency reduction exceeding 96%, and a user satisfaction rate of more than 97%. This demonstrates how Caps-PoR effectively enhances efficiency, security, and scalability in next-generation 6G networks, reshaping the future of resource management in decentralized systems.
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