A Novel Power-Aware Task Scheduling for Energy Harvesting-Based Wearable Biomedical Devices Using FPA

Yousri, Retaj; Elbayoumi, Mahmoud; Moawad, Ahmed W; Darweesh, M. Saeed; Soltan, Ahmed

doi:10.1109/icm52667.2021.9664945

Cited by 6 publications

(7 citation statements)

References 21 publications

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“…A set of validation experiments is conducted to compare the performance of FPA and SO optimization algorithms on the same problem. FPA showed in previous related work [8] its reliability on finding feasible schedules for a small number of N slots . It will be tested along with SO on finding feasible solutions but for a relatively larger number of time slots.…”

Section: Resultsmentioning

confidence: 98%

“…Several experiments are conducted to validate the performance of the snake optimizer technique for sensor task scheduling. Furthermore, the technique performance is compared with that of FPA (Flower Pollination Algorithm) [49] which was utilized in a prior study [8] for task scheduling. Implementation of SO, Hamming distance-based Tikhonov regularization, and all the experiments were done using MATLAB.…”

Section: Resultsmentioning

confidence: 99%

“…The strategy is based on adding a regularization term to the objective function in order to approach a particular solution with desirable properties [8]. This added term enforces the optimization algorithm to exclude the infeasible solutions by adding a penalty.…”

Section: Hamming-based Tikhonov Regularization Approachmentioning

confidence: 99%

“…This is because current systems are designed to give fixed performance, and it shut off whenever the energy is below a certain level. This requires fixed and stable energy source which is not the case for most of the energy harvesting technologies [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, task scheduling can be considered as a beneficial mechanism to manage the execution of various sensing tasks under limited, and time-varying harvested energy [14,19]. This can be crucial to maximize the performance in the context of continuous monitoring to avoid any interruption in the device operation [8]. Three main task scheduling algorithms were tested: the Dynamic Voltage and Frequency Scaling (DVFS), the decomposing and combining of tasks, and the duty cycling, to create the optimum order of task operation based on the available energy.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A power-aware task scheduler for energy harvesting-based wearable biomedical systems using snake optimizer

Yousri

Elbayoumi

Soltan

et al. 2023

Analog Integr Circ Sig Process

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There is an increasing interest in energy harvesting for wearable biomedical devices. This requires power conservation and management to ensure long-term and steady operation. Hence, task scheduling algorithms will be used throughout this work to provide a reliable solution to minimize energy consumption while considering the system operation constraints. This study proposes a novel power-aware task scheduler to manage system operations. For example, we used the scheduler to handle system operations, including heart rate and temperature sensors. Two optimization techniques have been used to illustrate the impact of task scheduling on energy consumption. The first is based on Snake Optimizer (SO), and the second is a greedy approach to compute the Hamming-based Tikhonov regularization. The FPA approach showed 50$$\%$$ % improvement in the convergence time for the scheduler.

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Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Hamming-based Tikhonov Regularization Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A power-aware task scheduler for energy harvesting-based wearable biomedical systems using snake optimizer

Yousri

Elbayoumi

Soltan

et al. 2023

Analog Integr Circ Sig Process

Self Cite

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Energy management for wearable medical devices based on gaining–sharing knowledge algorithm

Mohamed

Nomer

Yousri

et al. 2023

Complex Intell. Syst.

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Wearable devices are a growing field of research that can have a wide range of applications. The energy harvester is the most common source of power for wearable devices as well as in wireless sensor networks that require a battery-free operation. However, their power is restricted; consequently, power saving is crucial for wearable devices. Finding the best schedule for the various tasks that run on the wearable device can help to reduce power consumption. This paper presents a task scheduler for wearable medical devices based on Gaining–Sharing Knowledge (GSK) algorithm. The purpose of this task scheduler is to handle the tasks of a heart rate sensor and a temperature sensor to optimize the energy consumption throughout wearable medical devices. The proposed GSK-based scheduling algorithm is assessed against the state-of-the-art technique. The data used in our experiments are collected from an in-lab prototype.

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An Efficient DMO Task Scheduling Technique for Wearable Biomedical Devices

Mohamed

Elbayoumi

Yousri

et al. 2022

2022 International Conference on Microelectronics (ICM)

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A Novel Power-Aware Task Scheduling for Energy Harvesting-Based Wearable Biomedical Devices Using FPA

Cited by 6 publications

References 21 publications

A power-aware task scheduler for energy harvesting-based wearable biomedical systems using snake optimizer

A power-aware task scheduler for energy harvesting-based wearable biomedical systems using snake optimizer

Energy management for wearable medical devices based on gaining–sharing knowledge algorithm

An Efficient DMO Task Scheduling Technique for Wearable Biomedical Devices

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