Review of battery powered embedded systems design for mission-critical low-power applications

Malewski, Matthew; Cowell, David M. J.; Freear, Steven

doi:10.1080/00207217.2017.1409813

Cited by 9 publications

(8 citation statements)

References 20 publications

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“…For instance, in the context of low-power wide-area network communication technologies, LoRa (acronym of Long Range) is often considered as a suitable choice to develop a remote weather station ([ 25 , 26 ]), although there are also other technologies observed in the literature, such as WiFi [ 27 ] and Xbee [ 28 ]. Software optimization: the most used optimization strategy in this context is fine-tuning the operating system’s scheduling policy so as to reduce power consumption [ 29 ]. Other approaches include the adoption of smart software modules that, by avoiding the transmission of redundant values, can reduce the average data transmission rate, reducing the overall power consumption as a consequence [ 7 , 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

“…Software optimization: the most used optimization strategy in this context is fine-tuning the operating system’s scheduling policy so as to reduce power consumption [ 29 ]. Other approaches include the adoption of smart software modules that, by avoiding the transmission of redundant values, can reduce the average data transmission rate, reducing the overall power consumption as a consequence [ 7 , 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

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Design and Implementation of an Energy-Efficient Weather Station for Wind Data Collection

Leelavinodhan

Vecchio

Antonelli

et al. 2021

Sensors

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Agriculture faces critical challenges caused by changing climatic factors and weather patterns with random distribution. This has increased the need for accurate local weather predictions and weather data collection to support precision agriculture. The demand for uninterrupted weather stations is overwhelming, and the Internet of Things (IoT) has the potential to address this demand. One major challenge of energy constraint in remotely deployed IoT devices can be resolved using weather stations that are energy neutral. This paper focuses on optimizing the energy consumption of a weather station by optimizing the data collected and sent from the sensor deployed in remote locations. An asynchronous optimization algorithm for wind data collection has been successfully developed, using the development lifecyle specifically designed for weather stations and focused on achieving energy neutrality. The developed IoT weather station was deployed in the field, and it has the potential to reduce the power consumption of the weather station by more than 60%.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and Implementation of an Energy-Efficient Weather Station for Wind Data Collection

Leelavinodhan

Vecchio

Antonelli

et al. 2021

Sensors

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“…However, the battery capacity is limited. Some embedded systems that are deployed in distant areas require long-term operation [7,8]. In this case, these systems require periodic battery replacement to maintain running time.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Design of the Battery Initial Energy Level with Task Scheduling for Energy-Harvesting Embedded Systems

Miao

Wei

2021

Complexity

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When the energy-harvesting embedded system (EHES) is running, its available energy (harvesting energy and battery storage energy) seems to be sufficient overall. However, in the process of EHES task execution, an energy shortage may occur in the busy period such that system tasks cannot be scheduled. We call this issue the energy deception (ED) of the EHES. Aiming to address the ED issue, we design an appropriate initial energy level of the battery. In this paper, we propose three algorithms to judge the feasibility of the task set and calculate the appropriate initial energy level of the battery. The holistic energy evaluation (HEE) algorithm makes a preliminary judgment of the task set feasibility according to available energy and consumption energy. A worst-case response time-based initial energy level of the battery (WCRT-IELB) algorithm and an accurate cycle-initial energy level of the battery (AC-IELB) algorithm can calculate the proper initial battery capacity. We use the YARTISS tool to simulate the above three algorithms. We conducted 250 experiments on As Late As Possible (ALAP) and As Soon As Possible (ASAP) scheduling with the maximum battery capacities of 50, 100, 200, 300, and 400. The experimental results show that setting a reasonable initial energy level of the battery can effectively improve the feasibility of the task set. Among the 250 task sets, the HEE algorithm filtered 2.8% of them as infeasible task sets. When the battery capacity is set to 400, the WCRT-BIEL algorithm increases the success rates of the ALAP and ASAP by 17.2% and 26.8%, respectively. The AC-BIEL algorithm increases the success rates of the ALAP and ASAP by 18% and 26.8%, respectively.

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“…However, the battery capacity is limited. To ensure the reliability and long time running of real-time embedded system, the research is working on ways to reduce energy consumption, which can reduce system energy demands and improve the reliability and stability of energy supply [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A Group-Based Energy-Efficient Dual Priority Scheduling for Real-Time Embedded Systems

Liu

2020

Information

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As the limitation of energy consumption of real-time embedded systems becomes more and more strict, it has been difficult to ignore the time overhead and energy consumption of context switches for fixed-priority tasks with preemption scheduling (FPP) in multitasking environments. In addition, the scheduling for different types of tasks may disrupt each other and affect system reliability. A group-based energy-efficient dual priority scheduling (GEDP) is proposed in this paper. The GEDP isolates different types of tasks to avoid the disruption. Furthermore, it also reduces context switches effectively, thus decreasing system energy consumption. As many studies ignored the context switches’ overhead in the worst-case response time (WCRT) model, and it will affect the accuracy of WCRT, thereby affecting the system schedulability. Consequently, the WCRT model is improved based on considering context switches’ overhead. The GEDP is designed and implemented in Linux, and the time overhead and energy consumption of context switches is compared in different situations with GEDP and FPP. The experimental results show that GEDP can reduce context switches by about 1% and decrease energy consumption by about 0.6% for given tasks.

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Review of battery powered embedded systems design for mission-critical low-power applications

Cited by 9 publications

References 20 publications

Design and Implementation of an Energy-Efficient Weather Station for Wind Data Collection

Design and Implementation of an Energy-Efficient Weather Station for Wind Data Collection

Analysis and Design of the Battery Initial Energy Level with Task Scheduling for Energy-Harvesting Embedded Systems

A Group-Based Energy-Efficient Dual Priority Scheduling for Real-Time Embedded Systems

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