Energy Consumption Analysis of Edge Orchestrated Virtualized Wireless Multimedia Sensor Networks | Zendy

Tenager Mekonnen | Zendy; Miika Komu | Zendy; Roberto Morabito | Zendy; Tero Kauppinen | Zendy; Erkki Harjula | Zendy; Timo Koskela | Zendy; Mika Ylianttila | Zendy

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Energy Consumption Analysis of Edge Orchestrated Virtualized Wireless Multimedia Sensor Networks

Author(s) -

Tenager Mekonnen,

Miika Komu,

Roberto Morabito,

Tero Kauppinen,

Erkki Harjula,

Timo Koskela,

Mika Ylianttila

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2017.2783447

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

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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