Ann Based Route Optimization For Device-To-Device Iot Communication Using An Spectrum Aware Energy Efficient Routing Protocol

Abstract

In the modern era, A huge demand for Wireless mobile communication, sensors and cloud computing, the technologies of Internet of Things (IoT) been broadly used in logistics, Smart Measuring Device, Security of public, intelligent Construction and so on. IoT requires a routing mechanism that consumes less energy and Device to Device Communication. The expanding number of electronic gadgets alongside plenty of mixed media applications, for example, versatile gaming, High Definition (HD) films and video conferencing have triggered quick advances in IoT technology and services. A communication based on IoT necessitates a spectrum aware energy-efficient routing protocol (SAEER) to support the network and find the best route that consumes minimal energy. There is a limited energy resource provide to each node that is used as a communicating node but a reduction in energy occurs regularly. These phenomena create an energy hole in the IoT network, which disturbs the service to IoT applications. To overcome this problem, SAEER protocol is the key objective of routing protocols. In existing work, lots of researchers have formulated an energy-efficient routing protocol that selects the best route for end to end in the network but many of them do not detect malicious nodes in the network. In this paper, SAEER is introduced to detect the malicious or fail node and select the best route that consumes minimal energy consumption. The introduced routing protocol diminish the involvement of node between end to end in the network because of this here rate of energy consumption is minimal. Moreover, it provides not only a proficient way to a maximum capacity of routing but also a secure network for end to end communication. Therefore in our proposed work, we use a hybridization of Genetic Algorithm (GA) and Artificial Neural Network (ANN) is utilized for the secure routing in IoT network with novel fitness function. The QoS parameter is compared with proposed and existing Work based on numerous routing protocols and the outcomes validate the optimization by ANN. The results indicate that the introduced protocol assigns 8.77% less energy consumption and high throughput rate in comparison to existing work and it more than 92%.