Abstract
In recent years, smart cities have gained in popularity due to their potential to improve the quality of life for urban residents. In many smart city services, particularly those in the field of smart healthcare, big healthcare data is analyzed, processed, and shared in real time. Products and services related to healthcare are essential to the industry's current state, which increases its viability for all parties involved. With the increasing popularity of cloud-based services, it is imperative to develop new approaches for discovering and selecting these services. This paper follows a two-stage process. The first step involves designing and implementing an Internet-enabled healthcare system incorporating wearable devices. A new load-balancing algorithm is presented in the second stage, based on Ant Colony Optimization (ACO). ACO distributes tasks across virtual machines to maximize resource utilization and minimize makespan time. In terms of both makespan time and processing time, the proposed method appears to be more efficient than previous approaches based on statistical analysis.
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