Energy efficiency maximization in a wireless powered IoT sensor network for water quality monitoring

This study presents novel approaches to the allocation of resources in Internet-of-Things sensor network (IoTSN) systems applied to water-quality monitoring for optimal and more sustainable utilization of resources. To tackle the long-standing energy scarcity issue that currently plagues sensor network (SN) systems, energy harvesting is explored and exploited to maximize its untapped potential to develop asuccessive wireless power sensor network (WPSN) system embedded with a scheduling algorithm, and operate as a non-orthogonal multiple access (NOMA) system. Similarly, quality of service parameters are crucial design considerations for network efficiency,and energy efficiency (EE) is considered here. Consequently, an EE optimization problem is formulated for the successiveWPSN system and solved by exploiting the problem structure and through a meta-heuristic algorithm. The new system is validated through the numerical simulation results presented in this work by thoroughly analyzing, evaluating and comparing the proposed meta-heuristic based WPSN system with the baseline state-of-the-art WPSN systems that combined a meta-heuristic algorithm, two additional meta-heuristic algorithms including genetic algorithm (GA) and ant-colony optimization (ACO) algorithm as well as a non-meta-heuristic algorithm – specifically an iterative based Dinkelbach algorithm.The experimental outcomes show that the proposed system significantly outperforms the contemporary WPSN systems in terms of EE performance gains.http://www.elsevier.com/locate/comnet2022-05-22hj2021Electrical, Electronic and Computer Engineerin

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively