Energy Efficiency of Ultra-Low-Power Bicycle Wireless Sensor Networks Based on a Combination of Power Reduction Techniques

Sadik Kamel Gharghan,Rosdiadee Nordin,Mahamod Ismail

doi:10.1155/2016/7314207

Sadik Kamel Gharghan, Rosdiadee Nordin + Show 1 more

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https://doi.org/10.1155/2016/7314207

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Abstract

In most wireless sensor network (WSN) applications, the sensor nodes (SNs) are battery powered and the amount of energy consumed by the nodes in the network determines the network lifespan. For future Internet of Things (IoT) applications, reducing energy consumption of SNs has become mandatory. In this paper, an ultra-low-power nRF24L01 wireless protocol is considered for a bicycle WSN. The power consumption of the mobile node on the cycle track was modified by combining adjustable data rate, sleep/wake, and transmission power control (TPC) based on two algorithms. The first algorithm was a TPC-based distance estimation, which adopted a novel hybrid particle swarm optimization-artificial neural network (PSO-ANN) using the received signal strength indicator (RSSI), while the second algorithm was a novel TPC-based accelerometer using inclination angle of the bicycle on the cycle track. Based on the second algorithm, the power consumption of the mobile and master nodes can be improved compared with the first algorithm and constant transmitted power level. In addition, an analytical model is derived to correlate the power consumption and data rate of the mobile node. The results indicate that the power savings based on the two algorithms outperformed the conventional operation (i.e., without power reduction algorithm) by 78%.

Highlights

Wireless sensor networks (WSNs) consisting of several wireless nodes deployed in a vast area have the capacity to sense different events or parameters according to the type of application
The results reveal that the location estimated using the hybrid particle swarm optimization-artificial neural network (PSO-Artificial neural networks (ANNs)) algorithm outperforms the algorithms of previous studies [33, 51,52,53,54,55,56,57,58,59,60,61,62,63,64,65] in terms of mean absolute error (MAE)
The power consumption of a mobile node moving along a bicycle track was reduced through the use of two proposed algorithms: the transmission power control (TPC)-based accelerometer and the TPC-based distance estimation

Summary

Introduction

Wireless sensor networks (WSNs) consisting of several wireless nodes deployed in a vast area have the capacity to sense different events or parameters according to the type of application. The sensed parameters are determined using sensor nodes (SNs) and transmitted directly or through the router node to the coordinator node. The SNs, called motes in the WSN applications, are typically characterized by low power consumption, miniaturized size, and low cost [1]. The radio frequency unit of these nodes establishes communication between the nodes of the network and communication of the network with the outside world. The radio frequency and processing units consume the most energy [4]. Reducing the power consumption in the communication unit for these nodes is considered a major challenge in WSNs [5]. A transmission of one byte consumes more power than the power required to execute a thousand instructions [6, 7]

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