Adaptive EHTARA: An Energy-Efficient and Trust Aware Secure Routing Algorithm for Big Data Classification in IoT Network

Due to rapid growth and tremendous advancement, the Internet of Things (IoT) has been considered as a superior technology in recent years and increased its demand over the internet world because of its smart services. IoT has a wide range of applications over the industry, business, and academia. Still, security and routing remain a huge challenging task because of some reasons, such as heterogeneity issues, large energy consumption, and uncontrollable environment. In order to cope up with such security issues, it is essential to develop an energy-efficient routing protocol. Hence, this article presents an Adaptive energy harvesting and Trust aware routing (EHTARA) algorithm for optimal routing such that it prolongs the lifetime of the network. The optimal secure routing path is chosen to exploit the cost metric function. Moreover, the classification of big data is performed at MapReduce framework using stacked autoencoder, which is trained using the proposed Adaptive \(E^{2}\)-Bat algorithm. Moreover, the proposed Adaptive \(E^{2}\)-Bat algorithm is derived by incorporating adaptive principle with \(E^{2}\)-Bat algorithm. The proposed Adaptive EHTARA achieved an energy of 0.948 J that reveals the superiority of the proposed scheme.