Effective Task Scheduling in Critical Fog Applications Using Critical Task Indexing Scheduler (CTIS)

Document Type

Conference Proceeding

Source of Publication

2023 14th International Conference on Information and Communication Systems (ICICS)

Publication Date

11-23-2023

Abstract

To decrease time delay, energy consumption, and network utilization in the Internet of Things (IoT) is a key research area. The rapid advancement in IoT, leading to increase in size and cost makes traditional protocols and algorithms unfeasible to work with and requires redevelopment. Effective redevelopment may result in less energy consumption and resource utilization. Task scheduling algorithms on the Fog platform are one of the most time-consuming areas in IoT because it defines flow and queue for task processing. In time-critical applications like healthcare, an immediate response and access is required to the Fog platform. In that framework, this study evaluates a case study of healthcare applications to propose an efficient task scheduling algorithm known as Critical Task Indexing Scheduler (CTIS), that reduces the total time delay, energy consumption, and network utilization by indexing a task according to its criticality determined by its pre classified source. When compared with its predecessors such as First Come First Serve (FCFS), Shortest Job First (SJF), Critical Task First Scheduler (CTFS) and Cloud-only platforms, our proposed algorithm outperforms in all the three major parameters.

ISBN

979-8-3503-0786-3

Publisher

IEEE

Volume

00

First Page

1

Last Page

6

Disciplines

Computer Sciences

Keywords

Energy consumption, Machine learning algorithms, Protocols, Scheduling algorithms, Delay effects, Energy conservation, Medical services

Indexed in Scopus

no

Open Access

no

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