Abstract
This work presents a new approach to the maximization of energy and throughput in a wireless sensor network (WSN), with the intention of applying the approach to water-quality monitoring. Water-quality monitoring using WSN technology has become an interesting research area. Energy scarcity is a critical issue that plagues the widespread deployment of WSN systems. Different power supplies, harvesting energy from sustainable sources, have been explored. However, when energy-efficient models are not put in place, energy harvesting based WSN systems may experience an unstable energy supply, resulting in an interruption in communication, and low system throughput. To alleviate these problems, this paper presents the joint maximization of the energy harvested by sensor nodes and their information-transmission rate using a sum-throughput technique. A wireless information and power transfer (WIPT) method is considered by harvesting energy from dedicated radio frequency sources. Due to the doubly near–far condition that confronts WIPT systems, a new WIPT system is proposed to improve the fairness of resource utilization in the network. Numerical simulation results are presented to validate the mathematical formulations for the optimization problem, which maximize the energy harvested and the overall throughput rate. Defining the performance metrics of achievable throughput and fairness in resource sharing, the proposed WIPT system outperforms an existing state-of-the-art WIPT system, with the comparison based on numerical simulations of both systems. The improved energy efficiency of the proposed WIPT system contributes to addressing the problem of energy scarcity.
Highlights
Clean water is indispensable for human survival as it is used for drinking and hygiene and in agriculture and industry
Only g1 represents both a dedicated RF energy sources (DRFES) and an information receiver or base station. This is capable of both energy transmission and information reception to and from sensor nodes n and m, while other DRFES g can transmit energy to the sensor nodes n and m in their allocated time based on the knowledge of channel-state information (CSI)
The system considered the number of sensor nodes and the number of the DRFES as input parameters
Summary
Clean water is indispensable for human survival as it is used for drinking and hygiene and in agriculture and industry. The constant monitoring of water quality has become a necessity for safety of lives as stipulated by various standards organizational bodies such as the World Health Organization (WHO) and the European Union (EU). Monitoring guards against the supply of contaminated water. The traditional method used for water monitoring is confronted by several problems ranging from high cost, requirement of off-site analysis, time wasting, to interference from operators. To address these problems in a timely manner, wireless sensor network (WSN) technology is a promising economical approach which involves the deployment of different sensor nodes measuring water quality at a desired water-processing station.
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