Abstract
This paper introduces a fuzzy-based method that, according to the ratio of Throughput to Workload and the battery level, manages the sleeping time of devices in Wireless Sensor Networks (WSNs) for smart homes. The purpose of this work is a system that can be executed on off-the-shelf hardware and offers enhanced performance confronted with other approaches. The challenge here is to achieve a practical method that reaches the target while bypassing complex and computationally expensive solutions, which would diminish the possible applicability of the method in real scenarios. The retrieved results prove that the proposed approach outperforms other solutions, significantly prolonging the life of battery-powered wireless devices with also satisfactory values of the ratio Throughput to Workload. Besides, a proof-of-concept implementation on off-the-shelf devices confirms that the proposed method does not expect powerful hardware and can be surely implemented on a low-cost device.
Highlights
In the last few years, technological progress in the wireless communication, energy consumption, and chip miniaturization have facilitated the growth and the deployment of original applications based on Wireless Sensor Networks (WSNs) [1,2,3,4,5]
This paper introduces a solution based on fuzzy logic to cope with the energy consumption issue in battery-powered devices composing a WSN for smart homes
The Fuzzy Logic Controller (FLC) introduced in this paper considers three Membership Function (MF) (Low, Medium, High) for the input variables
Summary
In the last few years, technological progress in the wireless communication, energy consumption, and chip miniaturization have facilitated the growth and the deployment of original applications based on Wireless Sensor Networks (WSNs) [1,2,3,4,5]. Typical WSNs are not complicated monitoring systems, whose applications embrace environment monitoring [12], infrastructure security [13], industrial sensing [14] and intelligent transportation systems [15]. In these WSNs, sensors collect the demanded information, frequently according to a fixed temporal schedule, and transmit it to the sink, which interfaces with a server or a computer. The power consumption represents a crucial problem in WSNs. For instance, a battery-operated sensor device that wakes up once every few minutes to examine an environmental parameter requires to spend as little power as possible to lessen the battery replacement. The extension of the network lifetime is a critical issue
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