Design and Develop A Delay Sensitive Smart Health Framework Using Nature Inspired Load Balancer

Abstract

A smart healthcare system that uses fog computing and the internet of things is of paramount importance at the present time. Managing the ever-increasing load on fog nodes can be especially challenging in dynamic and diverse fog networks due to the high potential for overhead. As the number and variety of IoT-based devices grow, so ensure their processing requirements; this is where fog computing comes in. Delay in providing medical attention can have severe consequences. In order to address this issue, a delay-sensitive smart health framework has been proposed in this study. The framework uses a nature-inspired load balancer based on ant colony optimization algorithm, which primarily aims to decrease delay and performance issues. The Ant Colony Optimization Technique is a nature-inspired technique that improves system efficiency by balancing loads, decreasing response times, and minimizing delay. Our proposed approach is superior to the state-of-the-art in all these important metrics: latency, response time, overall system accuracy, and system stability. This will result in faster response times and improved medical services for patients in emergency situations.