Cost-Aware Resource Optimization for Efficient Cloud Application in Smart Cities

In this generation of smart computing environment, every device in the system and multple system are interconnected to each other, which allows users to view, analyze data, and make smart decisions. Smart cities are one example of smart environments where every device is connected and computing is performed on the cloud. In such a situation, the system requires an efficient system to handle huge requests and deliver data. Cloud computing plays an essential role in solving this issue but suffers from resource optimization, cost optimization, and load balancing. This work is aimed at solving the issue of resource and cost optimization in cloud infrastructure to provide a high service rate and sustainable infrastructure to cloud applications in smart cities. The proposed model is inspired by artificial neural networks and nature-inspired algorithm to reduce execution cost, average start time, and finish time and to make the system power efficient at the same time to improve the utilization of the system. The result shows that the proposed model completes more tasks in the least time and execution cost as compared to the existing models. This showcases the smart cloud applications are cost efficient and can complete the tasks in less time.