Internet of Things (IoT) has become one of the significant principles with the huge acceptance of an intelligent environments. An IoT is a collection of number of sensors combined through an internet to share the communication. In large-scale IoT network, the data is obtained from Wireless Sensor Networks (WSN) and it is forward from sink to the following processing stage of IoT. In this research, the Mountain Gazelle Optimization (MGO) algorithm is proposed for obtaining an energy efficient Cluster Head (CH) selection and routing in IoT. The consumption of energy in IoT is achieved by the optimal routing method by utilizing the optimization algorithm. The optimization-based clustering and routing approach is developed for designing the optimal transmission path by CH to destination. The performance of the proposed MGO method attains better results and it achieves the Packet Loss Rate of 17.6, End-to-End delay of 0.0597, No. of clusters formed of 49, Lifetime of 7 and Throughput of 2.5 with the No. of nodes of 800 when compared to the existing methods like Krill Herd Optimization (KHO), Lightening Search Algorithm (LSA), Lion Optimization Algorithm (LOA) and Particle Swarm Optimization (PSO)-LSA.