Cluster Head Selection Framework for Risk Awareness Enabled IoT Networks Using Ant Lion Optimisation Approach

Owing to the ability to enable an extensive range of applications, Internet of Things (IoT) receives huge research interest and it has major influence on ubiquitous computing. In retaining a useful network lifetime during Cluster Head Selection (CHS), many research challenges are encountered under constrains imposed by means of the limited energy, which are inherent in the small, locally-powered sensor nodes. The main aim of this research work is to investigate the CHS mechanism to solve the base station positioning problem and to balance the energy consumption in IoT. To extend the existence of the IoT, a Secured energy efficient method is essential. Since, data transmission, data processing and sensing by sensor nodes needs high energy, the sensor node become dead because of the presence of the rechargeable batteries. To overcome this issue, a security constraint CHS approach is implemented and it is known as Ant Lion Optimisation Approach (ALOP) approach. This approach is exploited to reach the objectives namely decreasing the energy, delay and distance as well as increasing the security. Further, the experimental analysis states that the proposed ALOP method outperforms the conventional methods.