Economic analysis of smart city infrastructure upgrades for sustainable development modeling in digital twin: Hybrid fog technique to improve system reliability

Fog computing would be an evolving idea extending the conventional cloud computing via taking advantage of the sources located on the sites of consumers in order to provide more effective services. Most real-time applications prefer it for its benefits, including lower operating prices and reduced network delay, and enhanced security. Resource allocation (RA) and planning are difficult tasks because of the heterogeneity of fog devices. A MA (MA) algorithm named the crow search algorithm (CSA) is used in the current study to meet RA and planning in fog computing environments. The suggested model focuses on 2 purposes: the achievement rate and the security hit rate. It is essential to maximize both purposes. A local search layout has been used for enhancing the efficiency of the CSA. RA and planning in fog environments are solved using the metaheuristic method. Based on the digital twin model simulations, the efficiency of the developed algorithm is compared to the current methods and demonstrates that the developed algorithms achieve the outlined purposes more efficiently.