Opportunistic Network Model with Gray Wolf Algorithm Based Multipath Routing in IoT Environment

The Internet of Things (IoT) is the kind of network that communicates and combines the network, which includes even a small smart device. This technology is the connection of smarter devices that greatly improves the standard of any human hand. Advantages of using the technology in real-time applications but still it consists of certain drawbacks in achieving maximum quality among the devices. The major drawbacks concentrated here are routing issues and path selection issues. To improve the network from such flaws in this article, an opportunistic network model with grey wolf algorithm-based multipath routing (QGWMR-IoT) is developed. The core processes are multipath routing protocol and optimal path selection process. With the presence of these methods, the efficiency and reliability of a network are at their maximum, and that leads to an increase in the efficiency of the network. Using characteristics focused on performance measurement of network throughput, network latency, routing overhead, transmission accuracy, and energy efficiency, the QGWMR-IoT network structure is implemented using the program ns3. It has been demonstrated that the suggested QGWMR-IoT operates more effectively and accurately during transmission.