Fog Based Architecture and Load Balancing Methodology for Health Monitoring Systems

Asghar, Anam; Abbas, Abdulla; Khattak, Hasan Ali; Khan, Samee U.

doi:10.1109/access.2021.3094033

Cited by 56 publications

(28 citation statements)

References 39 publications

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“…The behavior evaluation of the suggested EEIoMT framework was performed against CHTM [ 31 ], LBS [ 29 ], and FNPA [ 30 ], which are high-level models, and outcomes are shown in this part. The following performance metrics are used in the performance evaluation: Average energy consumption: This is the overall energy utilized by the entire system.…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, this system does not support mobility awareness. Asghar et al [ 29 ] presented a fog-relaying architecture for a health tracking system to reduce network usage and latency. When the health monitoring system is widely deployed, they also suggested a novel Load Balancing Scheme (LBS) to help fog nodes manage their load.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast to previous research, we ran extensive simulations using four distinct topology configurations and compared the outcomes to the best three fog-based implementations: CHTM, LBS, and FNPA models. The proposed EEIoMT outperformed the CHTM [ 31 ], LBS [ 29 ], and FNPA [ 30 ] models in four parameters: latency, energy consumption, network usage, and CPU usage.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System

Alatoun

Matrouk

Mohammed

et al. 2022

Sensors

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In healthcare, there are rapid emergency response systems that necessitate real-time actions where speed and efficiency are critical; this may suffer as a result of cloud latency because of the delay caused by the cloud. Therefore, fog computing is utilized in real-time healthcare applications. There are still limitations in response time, latency, and energy consumption. Thus, a proper fog computing architecture and good task scheduling algorithms should be developed to minimize these limitations. In this study, an Energy-Efficient Internet of Medical Things to Fog Interoperability of Task Scheduling (EEIoMT) framework is proposed. This framework schedules tasks in an efficient way by ensuring that critical tasks are executed in the shortest possible time within their deadline while balancing energy consumption when processing other tasks. In our architecture, Electrocardiogram (ECG) sensors are used to monitor heart health at home in a smart city. ECG sensors send the sensed data continuously to the ESP32 microcontroller through Bluetooth (BLE) for analysis. ESP32 is also linked to the fog scheduler via Wi-Fi to send the results data of the analysis (tasks). The appropriate fog node is carefully selected to execute the task by giving each node a special weight, which is formulated on the basis of the expected amount of energy consumed and latency in executing this task and choosing the node with the lowest weight. Simulations were performed in iFogSim2. The simulation outcomes show that the suggested framework has a superior performance in reducing the usage of energy, latency, and network utilization when weighed against CHTM, LBS, and FNPA models.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System

Alatoun

Matrouk

Mohammed

et al. 2022

Sensors

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“…High service response delay is one of the limitations of Cloud-based healthcare IoT applications. To solve this problem, Asghar et al [ 49 ] proposed a fog-based healthcare IoT architecture framework. Moreover, to adaptive for large-scale healthcare applications, they also introduce an efficient offloading schema to load balancing between fog servers.…”

Section: Survey Of Recent Iot Healthcare Applicationsmentioning

confidence: 99%

Smart healthcare IoT applications based on fog computing: architecture, applications and challenges

Quy

Nguyen

Anh

et al. 2021

Complex Intell. Syst.

106

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The history of human development has proven that medical and healthcare applications for humanity always are the main driving force behind the development of science and technology. The advent of Cloud technology for the first time allows providing systems infrastructure as a service, platform as a service and software as a service. Cloud technology has dominated healthcare information systems for decades now. However, one limitation of cloud-based applications is the high service response time. In some emergency scenarios, the control and monitoring of patient status, decision-making with related resources are limited such as hospital, ambulance, doctor, medical conditions in seconds and has a direct impact on the life of patients. To solve these challenges, optimal computing technologies have been proposed such as cloud computing, edge computing, and fog computing technologies. In this article, we make a comparison between computing technologies. Then, we present a common architectural framework based on fog computing for Internet of Health Things (Fog-IoHT) applications. Besides, we also indicate possible applications and challenges in integrating fog computing into IoT Healthcare applications. The analysis results indicated that there is huge potential for IoHT applications based on fog computing. We hope, this study will be an important guide for the future development of fog-based Healthcare IoT applications.

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“…In strong privacy legislation, e.g., GDPR, the data owner's consent needs to be asked. The consent of data sharing and its use needs to be renewed, which provides meaningful incentives [9].…”

Section: Introductionmentioning

confidence: 99%

An Attribute-Based Access Control for IoT Using Blockchain and Smart Contracts

et al. 2021

Self Cite

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With opportunities brought by the Internet of Things (IoT), it is quite a challenge to maintain concurrency and privacy when a huge number of resource-constrained distributed devices are involved. Blockchain have become popular for its benefits, including decentralization, persistence, immutability, auditability, and consensus. Great attention has been received by the IoT based on the construction of distributed file systems worldwide. A new generation of IoT-based distributed file systems has been proposed with the integration of Blockchain technology, such as the Swarm and Interplanetary File System. By using IoT, new technical challenges, such as Credibility, Harmonization, large-volume data, heterogeneity, and constrained resources are arising. To ensure data security in IoT, centralized access control technologies do not provide credibility. In this work, we propose an attribute-based access control model for the IoT. The access control lists are not required for each device by the system. It enhances access management in terms of effectiveness. Moreover, we use blockchain technology for recording the attribute, avoiding data tempering, and eliminating a single point of failure at edge computing devices. IoT devices control the user’s environment as well as his or her private data collection; therefore, the exposure of the user’s personal data to non-trusted private and public servers may result in privacy leakage. To automate the system, smart contracts are used for data accessing, whereas Proof of Authority is used for enhancing the system’s performance and optimizing gas consumption. Through smart contracts, ciphertext can be stored on a blockchain by the data owner. Data can only be decrypted in a valid access period, whereas in blockchains, the trace function is achieved by the storage of invocation and the creation of smart contracts. Scalability issues can also be resolved by using the multichain blockchain. Eventually, it is concluded from the simulation results that the proposed system is efficient for IoT.

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Fog Based Architecture and Load Balancing Methodology for Health Monitoring Systems

Abstract: This paragraph of the first footnote will contain support information, including sponsor and financial support acknowledgment.

Cited by 56 publications

References 39 publications

A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System

A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System

Smart healthcare IoT applications based on fog computing: architecture, applications and challenges

An Attribute-Based Access Control for IoT Using Blockchain and Smart Contracts

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