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Open AccessArticle

Resource Optimization Techniques and Security Levels for Wireless Sensor Networks Based on the ARSy Framework

1
Electrical Engineering and Computer Science, Kanazawa University, Ishikawa 920-1192, Japan
2
Informatic Engineering and Computer Education, State University of Makassar, Makassar 90222, South of Sulawesi, Indonesia
*
Authors to whom correspondence should be addressed.
Sensors 2018, 18(5), 1594; https://doi.org/10.3390/s18051594
Received: 3 April 2018 / Revised: 11 May 2018 / Accepted: 15 May 2018 / Published: 17 May 2018
(This article belongs to the Section Sensor Networks)
Wireless Sensor Networks (WSNs) with limited battery, central processing units (CPUs), and memory resources are a widely implemented technology for early warning detection systems. The main advantage of WSNs is their ability to be deployed in areas that are difficult to access by humans. In such areas, regular maintenance may be impossible; therefore, WSN devices must utilize their limited resources to operate for as long as possible, but longer operations require maintenance. One method of maintenance is to apply a resource adaptation policy when a system reaches a critical threshold. This study discusses the application of a security level adaptation model, such as an ARSy Framework, for using resources more efficiently. A single node comprising a Raspberry Pi 3 Model B and a DS18B20 temperature sensor were tested in a laboratory under normal and stressful conditions. The result shows that under normal conditions, the system operates approximately three times longer than under stressful conditions. Maintaining the stability of the resources also enables the security level of a network’s data output to stay at a high or medium level. View Full-Text
Keywords: Wireless Sensor Networks; ARSy framework; resource aware; security aware; security levels; mining data; adaptable system Wireless Sensor Networks; ARSy framework; resource aware; security aware; security levels; mining data; adaptable system
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MDPI and ACS Style

Parenreng, J.M.; Kitagawa, A. Resource Optimization Techniques and Security Levels for Wireless Sensor Networks Based on the ARSy Framework. Sensors 2018, 18, 1594.

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