A Novel Cost-Efficient Framework for Critical Heartbeat Task Scheduling Using the Internet of Medical Things in a Fog Cloud System

Abstract

Recently, there has been a cloud-based Internet of Medical Things (IoMT) solution offering different healthcare services to wearable sensor devices for patients. These services are global, and can be invoked anywhere at any place. Especially, electrocardiogram (ECG) sensors, such as Lead I and Lead II, demands continuous cloud services for real-time execution. However, these services are paid and need a lower cost-efficient process for the users. In this paper, this study considered critical heartbeat cost-efficient task scheduling problems for healthcare applications in the fog cloud system. The objective was to offer omnipresent cloud services to the generated data with minimum cost. This study proposed a novel health care based fog cloud system (HCBFS) to collect, analyze, and determine the process of critical tasks of the heartbeat medical application for the purpose of minimizing the total cost. This study devised a health care awareness cost-efficient task scheduling (HCCETS) algorithm framework, which not only schedule all tasks with minimum cost, but also executes them on their deadlines. Performance evaluation shows that the proposed task scheduling algorithm framework outperformed the existing algorithm methods in terms of cost.

An IoT-Based Healthcare Platform for Patients in ICU Beds During the COVID-19 Outbreak

“…The authors in [36] propose a fog-based framework in order to provide real-time task scheduling. The main issue is the fact that some information on healthcare is time sensitive such as ECG.…”

Dynamic Application Partitioning and Task-Scheduling Secure Schemes for Biosensor Healthcare Workload in Mobile Edge Cloud

“…It effectively and dynamically searches for optimal solutions for resource allocation among all candidate solutions, and this process continues until the final optimal solution is produced. An energy-efficient workflow and independent task scheduling based on cloud speed and power consumption-based frameworks is proposed in [11,[13][14][15][16]. The main goal of these studies is to minimize energy consumption and idle time while performing task scheduling.…”

“…The DAPWTS algorithm is iterative. Previously proposed application-partitioning frameworks [11,[13][14][15] have n 6 and n 7 time complexities to reduce the energy and response time of applications. The proposed work has the n 5 time complexity mentioned above while solving the offloading and scheduling problem of mobile workflow applications.…”

Microservice Based Computational Offloading Framework and Cost Efficient Task Scheduling Algorithm in Heterogeneous Fog Cloud Network

“…Resource cost includes storage and computing model reduced via task scheduling inhomogeneous cloud environment. The studies [16], [17] were investigated by resource models in the mobile cloud system for mobile applications. Whereas, the different pricing models discussed in these studies.…”

“…• Baseline 3: We implement the existing cost-efficient static task scheduling strategies [17], [18] without task scheduling in the experiment part, and test their performance as compared to the proposed scheme in term of application costs.…”