Routing Overhead Aware Optimal Cluster based Routing Algorithm for IoT Network using Heuristic Technique

Globally, billion of devices in heterogeneous networks are interconnected by the Internet Things (IoT). IoT applications require a centralized decision-making system due to failure-prone connectivity and high latency such system. Low-latency communications primary characteristic applications. Since usually have small payload sizes, reducing communication overhead is crucial improving energy efficiency. Researchers proposed several methods resolve load balancing issue reduce overhead. Although these techniques not effective, terms costs, end-to-end delay, packet loss ratio, throughput, node lifetimes negatively impact network performance. In this paper, we propose aware optimal cluster-based (COOC) routing algorithm for based on hybrid heuristic technique. Using three benchmark algorithms, form load-balanced clusters using k-means clustering, fuzzy logic, genetic algorithm. next step, compute rank each cluster multiple design constraints, which optimized improved COOT bird optimum search (I-COOT). After that, choose head (CH) according condition, thereby networks. Additionally, chaotic golden optimization (CGSO) choosing best path between nodes among paths ensure data transfer from CHs. To conclude, validate our COOC against different simulation scenarios compare results with existing state-of-the-art algorithms.