ArticleSensors (Basel, Switzerland)2020
A Novel Cost-Efficient Framework for Critical Heartbeat Task Scheduling Using the Internet of Medical Things in a Fog Cloud System.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Heart patient health monitoring system using invasive and non-invasive measurement.Scientific reports · 2024Article
- Delay Optimal Schemes for Internet of Things Applications in Heterogeneous Edge Cloud Computing Networks.Sensors (Basel, Switzerland) · 2022Article
- A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System.Sensors (Basel, Switzerland) · 2022Article
- Novel DERMA Fusion Technique for ECG Heartbeat Classification.Life (Basel, Switzerland) · 2022Article
- Smart-Contract Aware Ethereum and Client-Fog-Cloud Healthcare System.Sensors (Basel, Switzerland) · 2021Article
- An IoT-Based Healthcare Platform for Patients in ICU Beds During the COVID-19 Outbreak.IEEE access : practical innovations, open solutions · 2021Article
- Arousal Detection in Elderly People from Electrodermal Activity Using Musical Stimuli.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.