Energy-aware lazy scheduling algorithm for energy-harvesting sensor nodes

Severini, Marco; Squartini, Stefano; Piazza, Francesco

doi:10.1007/s00521-012-1088-x

Cited by 22 publications

(12 citation statements)

References 23 publications

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“…Furthermore, unlike [16], we maintain a general validity of the model removing hardware dependencies and avoiding over-simplifications. Regarding the scheduling and allocation policy instead, we consider an intermediate approach between [14] and [19], by exploiting DVFS and the heterogeneous architecture of the CPU of the computing system. Finally, in our experimental setup, similarly to [8], we tested the system in a real environment, considering the weather forecast as input for the energy budget computation and adapting the system performance limits, at run-time, accordingly.…”

Section: Discussionmentioning

confidence: 99%

“…The algorithm, therefore, computes the schedule and set the working mode, taking into account the timing requirements and the energy availability. Authors of [14] improved this work, by introducing relevant changes to the energy management and reducing the computational complexity. Similarly, in [19] the authors presented an algorithm on the Early Deadline First (EDF) scheduler, which exploits Dynamic Voltage and Frequency (DVFS) to manage the performance-power trade-off.…”

Section: B Energy-aware Scheduling Algorithmsmentioning

confidence: 99%

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Predictive Resource Management in Energy-constrained Embedded Systems

Crippa

Massari

Reghenzani

et al. 2020

2020 23rd Euromicro Conference on Digital System Design (DSD)

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The current trends in Internet of Things (IoT) lead to the deployment of low-power devices covering a wide range of application scenarios. These devices have the goal of executing simple tasks, automatically, usually with strict requirements in terms of space and cost. Typically, these devices have to rely on batteries or by harvesting energy devices (e.g., solar panels), in order to operate. On the other hand, IoT devices may be equipped with powerful multi-core CPUs to achieve performance goals, making the management of the energy budget a challenging task. This requires the development of an effective management system, that takes into account current and future energy budget availability, to dynamically bound the actual allocation of processing resources. Specifically, when exploiting solar panels for power supply, we can leverage on the weather forecast, to estimate the availability of energy in the near future. This paper introduces a predictive energy budget management system, targeting multi-core based embedded platforms. Thanks to both local and large-scale weather information, our solution aims at predicting the future incoming power and, accordingly, tuning the exploitable performance level to keep the system running under any environmental condition.

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Section: Discussionmentioning

confidence: 99%

Section: B Energy-aware Scheduling Algorithmsmentioning

confidence: 99%

Predictive Resource Management in Energy-constrained Embedded Systems

Crippa

Massari

Reghenzani

et al. 2020

2020 23rd Euromicro Conference on Digital System Design (DSD)

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“…In the light of the better coverage properties attainable with a 169MHz-based communication [21], and considering the importance of such feature specially for those situations where meter locations are severely constrained, the authors are allowed to conclude that the WM-Bus N modes surely represent the best trade-off for the applicative context under study. Future efforts will be targeted to the integration of energy-aware task scheduler to optimally 8 http://www.smart-material.com/ manage the tasks execution in sensor node processors [18], the employment of adaptive solutions to improve harvesting efficiency [22] and the development of full WSNs based on WM-Bus sensors, for metering scenarios first, and for water grid leakage monitoring ones then.…”

Section: Discussionmentioning

confidence: 99%

Wireless M-Bus sensor nodes in smart water grids: The energy issue

Squartini

Gabrielli

Mencarelli

et al. 2013

2013 Fourth International Conference on Intelligent Control and Information Processing (ICICIP)

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Smart Metering is one of the key issues in modern energy efficiency technologies. Several efforts have been recently made in developing suitable communication protocols for metering data management and transmission, and the Metering-Bus (M-Bus) is a relevant standard example, with a wide diffusion in the European market. This paper deals with its wireless evolution, namely Wireless M-Bus (WM-Bus), and in particular looks at it from the energy consumption perspective. Indeed, specially in those applicative scenarios where the grid powering is not available, like in water and gas metering settings, it is fundamental to guarantee the sustainability of the meter itself, by means of long-life batteries or suitable energy harvesting technologies. The present work analyzes all these aspects directly referring to a specific HW/SW implementation of the WM-Bus variants, providing some useful guidelines for its application in the smart water grid context.

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“…Even better outcomes are expected, when the prototype nodes will feature an optimized design and firmware implementation of the standard. Future efforts will be targeted to the integration of energyaware task scheduler [32][33][34] to optimally manage the tasks execution in sensor node processors, the employment of adaptive energy harvesting solutions to improve the node sustainability, and the development of full WSNs based on WM-Bus sensors, for metering scenarios first, and water leakages monitoring then.…”

Section: Final Remarks and Conclusionmentioning

confidence: 99%

Wireless M-Bus Sensor Networks for Smart Water Grids: Analysis and Results

Spinsante

Squartini

Gabrielli

et al. 2014

International Journal of Distributed Sensor Networks

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Wireless sensor network technologies are experiencing an impressive development, as they represent one of the building blocks upon which new paradigms, such as Internet of Things and Smart Cities, may be implemented. Among the different applications enabled by such technologies, automatic monitoring of the water grid, and smart metering of water consumptions, may have a great impact on the preservation of one of the most valued, and increasingly scarce, natural resources. Sensor nodes located along water pipes cannot rely on the availability of power grid facilities to get the necessary energy imposed by their working conditions. In this sense, an energy-efficient design of the network architecture, and the evaluation of Energy Harvesting techniques to sustain its nodes, becomes of paramount importance. This paper investigates the suitability of a Wireless Metering Bus-based solution for the implementation of smart water grids, by evaluating network and node related performance, through simulations, prototype design, and experimental tests, which confirm the feasibility and efficiency of the proposal.

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Energy-aware lazy scheduling algorithm for energy-harvesting sensor nodes

Cited by 22 publications

References 23 publications

Predictive Resource Management in Energy-constrained Embedded Systems

Predictive Resource Management in Energy-constrained Embedded Systems

Wireless M-Bus sensor nodes in smart water grids: The energy issue

Wireless M-Bus Sensor Networks for Smart Water Grids: Analysis and Results

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