Development of Fog-based Dynamic Load Balancing Framework for Healthcare using Fog Computing

Abstract

Fog computing has become one of the leading technologies by conquering the many significant challenges in IoT, Big Data, and Cloud. Computing models are inclining toward Fog than Cloud due to faster processing. The numerous idle devices near the users help overcome the issue of latency found in the Cloud. Resource management through load balancing plays an essential role in efficient data processing. Based on the current pandemic situation, Emergency patient’s vital sign monitoring system for COVID and other variants is implemented with support of dynamic resource load balancing environment. Apart from this, previously, we have faced many such diseases such as plague and flu which were pandemic and have become normal diseases now. Apart from them, there are many critical conditions and diseases such as hypertension, kidney failure, heart attack, cancer, lung, and liver disease that need continuous monitoring. It is not feasible to treat all patients at the hospital as the count is increasing very speedily. There is a need for infrastructure to handle resource issues without any delay in the treatment of patients using the fog computing. The proposed approach DynaReLoad would provide prompt health services and prevent early deaths due to critical conditions. An immediate alert to the doctors will be generated when detecting any abnormality. The effectiveness of DynaReLoad has been analyzed with other load balancing algorithms to achieve a low latency with minimum MakeSpan, better scheduling time, and response time, maximizing load balancing level and resource utilization using iFogSim.