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Energy consumption analysis of edge orchestrated virtualized wireless multimedia sensor networks

Mekonnen, Tenager; Komu, Miika; Morabito, Roberto; Kauppinen, Tero; Harjula, Erkki; Koskela, Timo; Ylianttila, Mika (2017-12-14)

 
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https://doi.org/10.1109/ACCESS.2017.2783447

Mekonnen, Tenager
Komu, Miika
Morabito, Roberto
Kauppinen, Tero
Harjula, Erkki
Koskela, Timo
Ylianttila, Mika
Institute of Electrical and Electronics Engineers
14.12.2017

T. Mekonnen et al., "Energy Consumption Analysis of Edge Orchestrated Virtualized Wireless Multimedia Sensor Networks," in IEEE Access, vol. 6, pp. 5090-5100, 2018. doi: 10.1109/ACCESS.2017.2783447

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© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
doi:https://doi.org/10.1109/ACCESS.2017.2783447
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https://urn.fi/URN:NBN:fi-fe201804166558
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Abstract

Virtualization enabled by container-based technologies is a recently emerging concept in the integration of Internet of Things (IoT) and cloud computing. Due of their lightweight nature, container-based virtualization tools improve manageability of cloud-based IoT solutions by making it possible to update application software on the fly. Although different studies have demonstrated the feasibility of efficiently running container-based virtualization on low-power IoT nodes, the implication of doing so on battery-powered nodes has been overlooked. In this paper, we investigate how much energy overhead is generated by Docker-based virtualization on battery powered camera sensor nodes. In our scenario, camera nodes are most of the time in “power off”state to save energy. They are switched on for streaming video only when activity is detected by motion sensor nodes. By means of empirical measurement and subsequent analysis, we found that starting and closing of containers in the Docker platform adds-up roughly 13 percent power consumption overhead during the boot-up and shutdown of the camera nodes. Furthermore, the fixed overhead occurring from boot-up and shutdown procedures become negligible with longer video stream sessions.

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