Cluster Head Selection using Dingo Optimization Algorithm in Mobile Ad Hoc Network

Efficient Energy-Efficient Cluster Head Selection (EECHS) remains a critical issue in Mobile Ad Hoc Networks (MANETs), where the selection of an appropriate cluster head (CH) can significantly enhance power efficiency. Clustering in routing plays a vital role in optimizing MANET performance by coordinating pathways through various analytics and criteria. Nodes in MANETs form clusters to improve communication, employing strategies such as distributed clustering and cluster-based routing. Despite their application, these methods often suffer from complexity and high overhead, which compromise their effectiveness.This study proposes the Dingo Optimization Algorithm (DOA) as a viable solution to the EECHS problem. DOA inherits its exploration and exploitation processes from the natural behavior of dingoes, involving techniques such as pursuing, approaching, encircling, and pestering to identify the optimal CHs. Extensive experimental research conducted on the NS2 simulator demonstrates that the proposed method achieves a packet delivery ratio (PDR) of 96%, a throughput of 240 Kbps, and an energy consumption of 21 mJ for a network with 500 nodes. The simulation results and replication findings indicate that this strategy is particularly suitable for sensitive MANET applications, outperforming existing routing tactics in terms of efficiency and effectiveness.