A predictive energy-efficient adaptive routing methodology for Mobile Ad hoc Networks

Abstract

A Mobile Ad hoc Network (MANET) is a self-configuring, infrastructure-less network of mobile devices connected wirelessly. In this paper, a novel approach, the Predictive Energy-efficient Adaptive Routing Technique (PEAR) approaches to the infrastructure-less network of mobile devices, addressing the intrinsic challenges of MANETs. PEAR is a network management system that uses real-time predictive analytics to forecast and adapt to topological changes due to node mobility, ensuring robust and proactive route management. It incorporates energy-aware routing decisions, conserving battery life and extending operational longevity, and uses a multi-factor routing algorithm. PEAR ensures loop-free routing to minimize latency and maintain scalability, making it adept at handling the growing complexity of MANET applications. PEAR outperformed Mobile Ad hoc On-demand Routing, showing throughput improvements of 2.5% at 5 m/s and 3.125% at 30 m/s, routing overhead reductions of 66.67% at 5 m/s and 50% at 30 m/s, energy consumption decreases by 66.67% at 5 m/s and 55.56% at 30 m/s, and a significant reduction in average delay by 66.67% at 5 m/s and 55.56% at 30 m/s, proving its superior efficiency and reliability in mobile networks.