Enhanced Elephant Herd Optimization Based Cluster Head Selection to Optimize QoS Parameter In IoT Enable Health Care System

Due to rapid propagation of smart internet of things (IoT) devices and services. IoT has grew an impotence in healthcare field of 5G wireless communication networks and is unmoving in constant growth. Several challenges need to be solved which faced by IoT networks. In this current work, we have focused on reducing energy consumption by the sensor nodes of IoT network to improve the durability power of the network. In this work the main issue is to choose the furthermost appropriate cluster head to enhance energy efficiency in the commutations model of medical applications in IoT network. The main disadvantages of present cluster head approaches are not considering the number packet loss, which lead to erratic communication and drains the energy of IoT network. To choose best cluster head in IoT enable health care network, we drive a model called Enhance Elephant Herding Optimization (EEHO) based on several performance metrics such as active nodes, load temperature, residual energy, cost function. The purposed model consume less energy in terms of QoS and increasing the network life time and also more number nodes being active(alive) as compare to other algorithm.