Energy Aware Adaptive Sleep Scheduling and Secured Data Transmission Protocol to enhance QoS in IoT Networks using Improvised Firefly Bio-Inspired Algorithm (EAP-IFBA)
S Nithyanandh, Sudharsan Omprakash, D Megala, M. P. Karthikeyan
Abstract
Objectives: To propose a suitable bio-inspired algorithm for energy-aware adaptive sleep scheduling and secured data transmission in IoT networks. Machine learning with bio-inspired technique is employed to schedule sleep periods for sensor nodes to maximize the lifetime of the IoT network, minimize energy consumption, and ensure robust data security during attacks. Methods: Improvised Firefly Bio-Inspired Algorithm (IFBA) is employed for adaptive sleep scheduling, and Dynamic Key Distribution Management (DKDM) with the elliptic curve method is used for secured and reliable data transmission between sensor nodes. Enhanced Recurrent Neural Networks (ERNN) with the N-Key method is deployed to identify the abnormal patterns associated with attacks and topology changes. Mean Square Error Data Recovery (MSEDR) is utilized to evaluate the error in data recovery, and Q-Learning Technique (QLT) with action sets is used to identify the finest path to ensure fast transmission of data. OMNETC++ simulator software is used to evaluate the performance of the proposed EAP-IFBA IoT network protocol with baseline protocols such as IWD-ARP, ECC-ILEACH, and RLSSACDGP. Findings: The proposed EAP-IBFA sleep scheduling and secured data transmission algorithm outperforms the prevailing methods IWD-ARP, ECCILEACH, and RLSSA-CDGP with an energy depletion rate of 8%, 97.5% alive nodes, 98% network life span in an IoT environment, 97.6% data transmission speed, 98% quick sleep scheduling, and 96.5% robustness to attacks. Novelty: The comprehensive solution of EAP-IFBA enhances QoS in IoT sensor networks. The proven results show that the proposed novel sleep scheduling and secureddata transmission algorithm has the ability to address the challenges of prevailing methods IWD-ARP, ECC-ILEACH, and RLSSA-CDGP in terms of energy consumption, data security, and dynamic sensing of topology changes for efficient and reliable IoT deployments. Keywords: Energy Efficiency; IoT Networks; Sleep Scheduling; Secured Data Transmission; Machine Learning; Bio-Inspired Algorithm; Quality of Service