An Innovative Algorithm for Multipath Routing and Energy Efficiency in IoT Across Varied Network Topology Densities

Abstract

The biggest problem for IoT networks is sensor node data transport. Overuse of communication power shortens node lifespan. Therefore, network issues including QoS, security, network heterogeneity, congestion reduction, reliable routing, and energy efficiency must be addressed. Routing protocols are essential for corporate data transmission. Information collection and consolidation need data aggregation to minimize traffic congestion, operating expenses, energy usage, and network lifespan. Aggregating IoT data makes route planning dependable, energy-efficient, and difficult. NS2 simulation generated Disjoint & Scalable Multipath Routing (D &SMR), a novel routing architecture. The method measures delivery performance using decision trees and neural networks. During model training, we evaluate (D &SMR) routing scheme predictability, node popularity, power consumption, velocity, and location. Simulations show that (D &SMR) outperforms a reliable routing system in delivery success, message loss, overhead, and hop count. The proposed hybrid routing method includes cluster construction and intra-and inter-cluster routing. The research found that (D &SMR) outperforms previous studies in network resilience, packet transmission efficiency, latency, and energy usage.