Makespan Optimization of Workflow Application based on Bandwidth Allocation Algorithm in Fog-Cloud Environment

Abstract

Fog computing technology has emerged to handle the large amount of data generated by Internet of Things (IoT) terminals and cope with latency-sensitive application requests by allocating computation and storage resources at the edge of the Internet. In many IoT applications, the data acquisition procedures must apply the Directed Acyclic Graph (DAG) to get real-time results. The principal goal of DAG scheduling is to reduce total completion time without breaking priority constraints by properly allocating tasks to processors and arranging task execution sequencing. In this paper, we propose a bandwidth-aware workflow allocation (BW-AWA) that schedules tasks by priority to the resource that minimizes the total execution time (Makespan) in the entire heterogeneous computing system without affecting the increase in energy consumed. The task selection process needs to consider the dependency between tasks. The proposed approach is tested with a road safety case study, and the results are compared to well-known approaches to demonstrate the effectiveness in reducing the Makespan.

An Efficient Energy Makespan Optimization Based Task Mapping In Fog Enabled IoT Application

“…This proposed approach gives better performance in the execution time and the allocated memory compared with PSO and GA algorithms. Dougani et al [21] propose a Bird Swarm Optimization (BSO) algorithm for the dynamic scheduling of independent tasks to minimize makespan and improve. They considered a task-resource compatibility test to measure the compatibility of the tasks for the overloaded VMs with the underutilized VMs based on their available resources.…”

“…• In BLA [21], execution time is reduced in fog computing environment. But it does not support dynamic job scheduling.…”