Offload and Schedule Tasks in Health Environment using Ant Colony Optimization at Fog Master

Abstract

The time sensitivity of healthcare applications leads to the urgent need to process the data with minimum delay. The limited resources in end-user devices make offloading the tasks to the fog node to process them essential. Fog node can process the tasks near the end-user, which reduce the delay caused by offloading them into the cloud. Fog nodes in the fog layer can collaborate to process tasks. A balanced task schedule in the fog layer will make the fog nodes collaborate to reduce the response time. In this work, we start by computing a probability for each task to decide whether the task will offload to the fog master or not. This probability will allow the fog node to process some of the received tasks without the need for offloading. We only offload the tasks whose probability exceeds a threshold value to the fog master. The fog master run the Ant Colony Optimization algorithm to schedule the task to a suitable node in the fog layer. The simulation results show that the proposed load balancer provides better results in reducing the delay.