On the design of wireless sensor networks for autonomous heliostats in Solar Tower Power Plants

Cabezas, J.; Aguilar, E.; Pastor, Antonio; Mendez, A.; Torralba, A.; Carvajal, R.G.; Aranda, Eladio Durán; Viguera, J.

doi:10.1109/iecon.2012.6389098

Cited by 4 publications

(1 citation statement)

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“…These data serve at the shipping company's back-end to optimize a cargo's route and to provision spare parts [8]. Differently, sensors and actuators attached to solar panels can steer their operation based on current prices on the energy market, trading off a panel's wear and tear against monetary gains [9].…”

Section: Introductionmentioning

confidence: 99%

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

Mottola

Picco

Oppermann³

et al. 2019

IIEEE Trans. Software Eng.

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Abstract-A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language-also directly usable by WSN developers-and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype-including the complete tool-chain and underlying system support-sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions.

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Section: Introductionmentioning

confidence: 99%