Energy efficient and intelligent routing algorithm using DAI and self organizing map hybrid algorithm for future optical wireless communication

Wireless technology will advance with the launch of 6G, which will be essential for providing a dependable connection between sensing components in Internet of Things (IOT) applications. The next generation of intelligent transportation systems (ITS) will be greatly influenced by these two processes. A unique method for distributed neural networks (DAI) is proposed in the suggested study. To solve these issues, neural networks (NNs) are implemented for both quick responses for node intra-cluster interaction and energy-efficient routing. To balance the energy consumption of the sensor nodes, a better pheromone trail update scheme and route discovery algorithm are used. To optimise the route establishment, it makes use of an effective heuristic update technique that is based on a greedy predicted energy cost metric. Although there have been several studies on inter-cluster energy efficient networks, this study offers a novel way to implement the DAI and Self Organizing Map (SOM) hybrid methodology. The recommended approach turns out to be superior approach in terms of both the computational challenges and the overall network energy consumption. The report also provides a comparison with conventional justification techniques, simulation results, and mathematical analysis.