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Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices

Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices

Grzegorz Chmaj, Henry Selvaraj
Copyright: © 2016 |Volume: 4 |Issue: 1 |Pages: 17
ISSN: 2166-7160|EISSN: 2166-7179|EISBN13: 9781466693821|DOI: 10.4018/IJSI.2016010103
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MLA

Chmaj, Grzegorz, and Henry Selvaraj. "Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices." IJSI vol.4, no.1 2016: pp.31-47. http://doi.org/10.4018/IJSI.2016010103

APA

Chmaj, G. & Selvaraj, H. (2016). Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices. International Journal of Software Innovation (IJSI), 4(1), 31-47. http://doi.org/10.4018/IJSI.2016010103

Chicago

Chmaj, Grzegorz, and Henry Selvaraj. "Energy-Efficient Computing Solutions for Internet of Things with ZigBee Reconfigurable Devices," International Journal of Software Innovation (IJSI) 4, no.1: 31-47. http://doi.org/10.4018/IJSI.2016010103

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Abstract

Nowadays we are witnessing a trend with significantly increasing number of networked and computing-capable devices being integrated into everyday environment. This trend is expected to continue. With computing devices available as logic structures, they might use each other's processing capabilities to achieve a given goal. In this paper, the authors propose an architectural solution to perform the processing of tasks using a distributed structure of Internet of Things devices. They also include ZigBee devices that are not connected to the Internet, but participate with the processing swarm using local network. This significantly extends the flexibility and potential of the IoT structure, while being still not a well-researched area. Unlike many high-level realizations for IoT processing, the authors present a realization operating on the communications, computing and near protocol level that achieves energy consumption efficiency. They also include the reconfigurability of IoT devices. The authors' work is suitable to be the base for higher-level realizations, especially for systems with devices operating on battery power. At the same time, the architecture presented in this paper uses minimal centralization, moving maximum responsibilities to regular devices. The proposed realizations are described using linear programming models and their high efficiency is evaluated.

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