Enhanced Multi-path Energy-Efficient Routing with Dynamic Load Balancing for MANETs Using Bellman-Ford Algorithm

Abstract

Mobile Ad Hoc Networks (MANETs) play a crucial role in modern communication, particularly in dynamic and infrastructure-less environments such as disaster recovery, military operations, and IoT-based applications. However, traditional routing protocols like AODV, DSR, and DSDV face significant challenges, including high energy consumption, frequent route failures, and inefficient load balancing. The Bellman-Ford algorithm, despite its robustness in shortest-path computations, lacks energy-awareness, leading to rapid node depletion and network instability. To address these limitations, this study proposes an Enhanced Multi-path Energy-Efficient Routing (EMEER) with Dynamic Load Balancing, incorporating an optimized Bellman-Ford algorithm. The key novelties of this approach include an energy-aware routing metric that considers residual energy levels, a multi-path selection strategy to enhance fault tolerance, and a dynamic load-balancing mechanism that distributes traffic to prevent congestion. These enhancements collectively improve network reliability and longevity. The proposed EMEER protocol is implemented in a simulated MANET environment using NS-3, and its performance is evaluated against existing protocols. The results demonstrate that EMEER achieves a 25.6% reduction in energy consumption, a 17.3% improvement in packet delivery ratio (PDR), and a 31.8% increase in network lifetime compared to traditional approaches. Furthermore, it significantly reduces end-to-end delay and routing overhead. By integrating energy efficiency with adaptive load balancing, this study contributes to the development of more sustainable and resilient MANET architectures. Future work will explore the integration of AI-driven optimization techniques, inspired by hybrid metaheuristic models used in edge computing, to further enhance routing adaptability.