Optimizing Multi-Objective Routing with Quantum Firefly Algorithm in Wireless Sensor Networks

There are many different industries that make usage of WSN, which are fundamental to the IoT. The present state of technology has been changed by the Internet of Things. Various kinds of nodes for sensors might be linked by electronic devices that are capable to interact with each other via the Internet, such as recording devices, healthcare devices, and domestic appliances. So, these gadgets can only handle so much data, have so little storage space, and can only be powered when fully charged. Modern society relies heavily on WSN, which finds use in the production of thermal electricity in greenhouses as well, tracking the environment via hydraulic power stations, forest surveillance, and automobile manufacture. Traditional WSNs allow sensor nodes to send unprocessed information to a main hub, there it may be processed and stored. With the latest developments in IoT technology, WSN can now send raw data to fog nodes to be processed, stored, and computed locally, doing away with the requirement to send raw data to centralized servers altogether. Also included is a comprehensive analysis of the QFO-MOSR method in comparison to other methods already in use. The results definitively demonstrate that the QFO-MOSR model outperforms with overall accuracy of 93% compared to FEAR, P-SEP, QACMOR, and AFA in WSN with respect to an total of metrics, which includes energy efficiency, packet delivery ratio, and delay.