Distributed Intelligence Empowered 6G Networks: A Hybrid Optimization Perspective

This paper deals with architectural evolution related to the convergence of space-aerial-terrestrial-underwater communication systems and the infusion of distributed intelligence in 6G communication networks. Several challenges and prerequisites awaiting the deployment of 6G networks have been debated. In addition, the role of various new technologies including but not limited to AI, MEC, Fog Computing, and SDN in realizing the same has also been discussed in detail. The proposed smart architecture, based on the hybrid optimization algorithm, combines clustering algorithms as the backbone for PSO and GA. It is proposed to achieve improved resource allocation, energy efficiency, and reduced latency. The benchmark simulation results for clear-cut performances include a decrease in energy consumption and latency, hence proving the viability of the model in low-latency and energy-efficient applications. It will be able to provide state-of-the-art vision for how to architect and tailor communication systems toward a variety of future applications including, but not limited to, smart cities, industrial automation, and telepresence services.