Prioritized scheduling technique for healthcare tasks in cloud computing

Elshahed, Eman M.; Abdelmoneem, Randa M.; Shaaban, Eman; El-Zahed, H.; Al-Tabbakh, Shahinaz M.

doi:10.1007/s11227-022-04823-7

Cited by 7 publications

(3 citation statements)

References 47 publications

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“…The proposed method increases scheduling accuracy, enhancing healthcare systems' performance and effectiveness. Elshahed et al [21] proposed a new prioritized sorted task-based allocation (PSTBA) for healthcare monitoring systems. The virtual machine is used here to perform a particular task in monitoring systems.…”

Section: Related Workmentioning

confidence: 99%

Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities

Kaliappan

Gnanamurthy²,

Yahya

et al. 2023

Sustainability

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Smart healthcare using the cloud and the Internet of Things (IoT) allows for remote patient monitoring, real-time data collection, improved data security, and cost-effective storage and analysis of healthcare data. This paper proposes an information-centric dissemination scheme (ICDS) for smart healthcare services in smart cities. The proposed scheme addresses the time sensitiveness of healthcare data and aims to ensure consistent dissemination. The ICDS uses decision-tree learning to classify requests based on time-sensitive features, allowing prioritization of access. The scheme also involves segregating sensitive information and distributing digital health data within the classified time to retain time sensitiveness and prioritize access. The learning is then modified for the leaves based on data significance and minimum resources to reduce waiting times and improve availability.

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Section: Related Workmentioning

confidence: 99%

Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities

Kaliappan

Gnanamurthy²,

Yahya

et al. 2023

Sustainability

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show abstract

“…These studies aim to explore the potential bene ts of cloud computing for different application areas and to identify the challenges and opportunities associated with this approach. Some examples of these studies can be found in [20][21][22][23][24][25]. Overall, these efforts are aimed at advancing the development of cloud-based applications and improving their effectiveness and e ciency.…”

Section: Related Workmentioning

confidence: 99%

Integrating Semantic Web into Context-Aware Mobile Application based on Cloud Computing

Lai

Hsu

2023

Preprint

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The current context-aware mobile application approach lacks a standardized method for knowledge representation that can handle intelligence effects, such as automatic, dynamic, and intelligent support for mobile context-awareness applications. To tackle these intelligence issues, this research introduces the Semantic-aware Service into Cloud Computing Architecture (SSCCA) as a common scheme to enable intelligent context-aware mobile applications using a fundamental cloud service model. SSCCA combines Cloud Computing and Semantic Web research to facilitate the development of intelligent cloud computing applications. To validate the proposed approach, a Smart Context-aware Invoice Platform (SCIP), an intelligent cloud computing application built on SSCCA, is implemented to gather personal electronic invoices and offer context-aware mobile services on demand.

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“…Depending on the rate of congestion and priority of the data sensed, transmission is balanced using queuing or delivery as modeled in the decision mode. For real-time remote monitoring of the patient, Elshahed et al [17] propose a new task scheduling and allocation technique for healthcare monitoring implemented in IoT cloud-based architecture. The proposed technique performs a prioritized sorted task-based allocation scheme for selecting the best virtual machine to execute the health task, solving the problem of delay, missed tasks, and failure rate, and the guarantee ratio.…”

Section: Scheduling On Iomtmentioning

confidence: 99%

Design of Edge-IoMT Network Architecture with Weight-Based Scheduling

Tseng,

Chen,

Wen

2023

Sensors

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Population health monitoring based on the Internet of Medical Things (IoMT) is becoming an important application trend healthcare improvement. This work aims to develop an autonomous network architecture, collecting sensor data with a cluster topology, forwarding information through relay nodes, and applying edge computing and transmission scheduling for network scalability and operational efficiency. The proposed distributed network architecture incorporates data compression technologies and effective scheduling algorithms for handling the transmission scheduling of various physiological signals. Compared to existing scheduling mechanisms, the experimental results depict the network performance and show that in analyzing the delay and jitter, the proposed WFQ-based algorithms have reduced the delay and jitter ratio by about 40% and 19.47% compared to LLQ with priority queueing scheme, respectively. The experimental results also demonstrate that the proposed network topology is more effective than the direct path transmission approach in terms of energy consumption, which suggests that the proposed network architecture may improve the development of medical applications with body area networks such that the goal of self-organizing population health monitoring can be achieved.

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Prioritized scheduling technique for healthcare tasks in cloud computing

Cited by 7 publications

References 47 publications

Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities

Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities

Integrating Semantic Web into Context-Aware Mobile Application based on Cloud Computing

Design of Edge-IoMT Network Architecture with Weight-Based Scheduling

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