IoT energy efficiency routing protocol using FHO‐based clustering and improved CSO model‐based routing in MANET

Summary Many protocols, services, and electrical devices with built‐in sensors have been developed in response to the rapid expansion of the Internet of Things. Mobile ad hoc networks (MANETs) consist of a collection of autonomous mobile nodes that can form an ad hoc network in the absence of any pre‐existing infrastructure. System performance may suffer due to the changeable topology of MANETs. Since most mobile hosts operate on limited battery power, energy consumption poses the biggest challenge for MANETs. Both network lifetime and throughput improve when energy usage is reduced. However, existing approaches perform poorly in terms of energy efficiency. Scalability becomes a significant issue in large‐scale networks as they grow, leading to overhead associated with routing updates and maintenance that can become unmanageable. This article employs a MANET routing protocol combined with an energy conservation strategy. The clustering hierarchy is used in MANETs to maximize the network's lifespan, considering its limited energy resources. In the MANET communication process, the cluster head (CH) is selected using Fire Hawk Optimization (FHO). When choosing nodes to act as a cluster for an extended period, CH election factors in connectivity, mobility, and remaining energy. This process is achieved using an optimized version of the Ad hoc On‐Demand Distance Vector (AODV) routing protocol, utilizing Improved Chicken Swarm Optimization (ICSO). In comparison to existing protocols and optimization techniques, the proposed method offers an extended network lifespan ranging from 90 to 160 h and reduced energy consumption of 80 to 110 J, as indicated by the implementation results. This article addresses energy challenges in Mobile Ad Hoc Networks (MANETs) by integrating a routing protocol with an energy conservation strategy. Employing clustering hierarchy and Fire Hawk Optimization for Cluster Head selection, it optimizes the Ad Hoc On‐Demand Distance Vector (AODV) protocol using Improved Chicken Swarm Optimization. The proposed approach significantly enhances network lifespan (90‐160 hours) and reduces energy consumption (80‐110 joules) compared to existing protocols, providing an efficient solution for large‐scale MANETs with dynamic topologies and limited energy resources.