Dynamic energy-based multilayer routing framework for scalable and reliable IoT networks

Abstract

The exponential growth of the Internet of Things (IoT) demands scalable, energy-efficient, and reliable data routing strategies, especially within resource-constrained Wireless Sensor Networks (WSNs). This paper introduces DEBML (Dynamic Energy-Based Multilayer Routing), a novel distributed routing framework that addresses these challenges by organizing nodes into dynamic energy-based layers. Each layer is formed by grouping nodes with similar residual energy levels, enabling the application of layer-specific routing protocols that optimize energy usage and data delivery efficiency. High-energy layers handle time-sensitive and critical transmissions using robust routing, while lower-energy layers prioritize energy conservation for routine communication. A key innovation of DEBML is its dynamic re-layering mechanism, which continuously monitors energy levels and redistributes nodes across layers to maintain load balance and adapt to changing network conditions. Extensive simulations demonstrate that DEBML significantly outperforms existing methods in terms of packet delivery ratio, end-to-end delay, network lifetime, and overall energy efficiency. The proposed framework offers a scalable, adaptive, and energy-aware solution suitable for next-generation IoT applications such as smart healthcare, industrial monitoring, and environmental sensing.