Title: Fractional red panda optimisation-based cluster head selection and routing in IoT

Authors: Nandkumar Prabhakar Kulkarni; Meena Chavan; Amar Rajendra Mudiraj

Addresses: Computer Science and Engineering Department, MIT School of Computing, MIT Art, Design and Technology University, Rajbaugh Loni, Kalbhor, Pune 412201, Maharashtra, India ' Department of Electronics and Telecommunication Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, Maharashtra, India ' Cloud Infrastructure Lead, Accenture India Solutions Pvt Ltd., Pune, Maharashtra, India

Abstract: In the present world, the IoT has been developed as a widespread network for various smart devices in numerous applications. IoT is considered a significant technology for achieving the requirements for a variety of applications. However, load balancing, energy inadequate battery power and security may affect the performance of IoT. Therefore, the Fractional Red Panda Optimisation (FrRPO)-based Cluster Head (CH) selection and routing is proposed in this paper. The IoT network simulation is the primary process. The Deep Q Net (DQN) is utilised for predicting the energy. The FrRPO with fitness factors like predicted energy, delay and distance is used to select the CH. Moreover, the FrRPO with fitness factors like throughput, energy, distance and reliability is used for routing. The metrics like energy consumption, delay and throughput are considered to validate the model, which attains the optimal results of 0.555 J, 0.666 sec and 89.02 Mbps.

Keywords: cluster head; red panda optimisation; internet of things; routing; fractional calculus.

DOI: 10.1504/IJGUC.2026.150663

International Journal of Grid and Utility Computing, 2026 Vol.17 No.1, pp.1 - 15

Received: 09 Sep 2024
Accepted: 04 Dec 2024
Published online: 19 Dec 2025 *

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