Power Wireless Sensor Networks Research Articles

Hierarchical Deep Reinforcement Learning for Age-of-Information Minimization in IRS-Aided and Wireless-Powered Wireless Networks

In this paper, we focus on a wireless-powered sensor network coordinated by a multi-antenna access point (AP). Each node can generate sensing information and report the latest information to the AP using the energy harvested from the AP’s signal beamforming. We aim to minimize the average age-of-information (AoI) by adapting the nodes’ scheduling and the transmission control strategies jointly. To reduce the transmission delay, an intelligent reflecting surface (IRS) is used to enhance the channel conditions by controlling the AP’s beamforming strategy and the IRS’s phase shifting matrix. Considering dynamic data arrivals at different sensing nodes, we propose a hierarchical deep reinforcement learning (DRL) framework to for AoI minimization in two steps. The users’ transmission scheduling is firstly determined by the outer-loop DRL approach, e.g. the DQN or PPO algorithm, and then the inner-loop optimization is used to adapt either the uplink information transmission or downlink energy transfer to all nodes. A simple and efficient approximation is also proposed to reduce the inner-loop rum time overhead. Numerical results verify that the hierarchical learning framework outperforms typical baselines in terms of the average AoI and proportional fairness among different nodes.

Facebook Prophet Library prediction-based Energy Harvested MAC Protocol (FPEH-MAC)

Data transfer within severe time constraints is crucial for wireless sensor networks used in mission-critical applications, such as industrial control and disaster monitoring. In such applications, exceeding time constraints and facing limitations in longevity can pose threats to human life. The primary option for powering wireless sensor networks is to utilize ambient energy sources like solar energy, thermal energy, etc., which are abundant in nature The lifetime and latency of these networks depend on a well-implemented duty cycle-based MAC protocol, and maximizing the duty cycle is achieved through efficient utilization of harvested and residual energy. Since harvested energy is inherently unpredictable, appropriate forecasting techniques are required. In this study, a prediction-based Energy Harvested MAC protocol (FPEH-MAC) based on the Facebook Prophet library is proposed to maximize the predicted duty cycle of the MAC protocol by forecasting harvested and residual energy. Additionally, this MAC protocol demonstrates an increase in residual energy and duty cycle, ensuring an extended lifecycle for the wireless sensor network. The suggested protocol was evaluated for latency, throughput, percentage increase in residual energy, and packet delivery ratio using OMNET, INET, Python, and MATLAB. The results of the analysis indicate that the proposed technique increases residual energy by 1.2%, enhances throughput by 33.33%, and reduces latency by 9.6% when compared to previous work.

Optimize the Network Coding Paths to Enhance the Coding Protection in Wireless Multimedia Sensor Network

Efficient protection techniques for multimedia data transfer over Wireless Sensor Network (WSN) are very essential issues. In noisy Wireless Multimedia Sensor Networks (WMSN) Quality of Service (QoS) is a challenging task due to bandwidth and limited energy, and unpredictable channel conditions. Therefore, Forward Error Correction (FEC), a class of channel coding has been widely used in WSN. Nevertheless, the bulky size of multimedia data makes it more difficult to be transported over the noisy multi-hop wireless network. Moreover, the efficiency of FEC drops as the number of hops increases. In this paper, an optimized protection technique based on network coding and rateless code has been proposed to enhance the throughput and reduce overhead during data transfer in WMSN. The performance of NCP-OPR is enhanced via Optimal Network Path Model (ONPM) where the best available paths are optimally selected using Particle Swarm Optimization (PSO). In conjunction with the proposed protection scheme, the proposed ONPM is intended for limited power WSN by optimally distributing the power usage among the network paths so that the throughput can be improved.

Design and Implementation of Ambiently Powered Internet of Things-That-Think With Asynchronous Inference

This work offers design and implementation of in-network inference, using message passing among ambiently powered wireless sensor network (WSN) terminals. The stochastic nature of ambient energy harvesting dictates intermittent operation of each WSN terminal and as such, the message passing inference algorithms should be robust to asynchronous operation. It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, in-network message passing problem, often at the expense of increased total delay. Examples from Gaussian belief propagation and Average Consensus are provided, along with the derivation of a statistical convergence metric for the latter case. A k-means method is offered that maps the elements of the calculated vector to the different WSN terminals and overall execution delay (in number of iterations) is quantified. Interestingly, it is shown that there are divergent instances of the in-network message passing algorithms that become convergent, under asynchronous operation. Ambient solar energy harvesting availability is also studied, controlling the probability of successful (or not) message passing. Hopefully, this work will spark further interest for asynchronous message passing algorithms and technologies that enable in-network inference, towards ambiently-powered, batteryless Internet-of-Things-That-Think.

Performance Analysis of Solar Powered Wireless Sensor Network

Performance Analysis of Solar Powered Wireless Sensor Network

Research on Resource Allocation Strategies for Wireless Powered Sensor Network

Wireless powered sensor network (WPSN) solves the problem of difficult battery replacement of sensor nodes in some environments. The unreasonable distribution of network resources in the energy transmission environment will lead to a sharp decline in the energy collected by sensor nodes, reduce the network life, and cause resource waste. In this paper, by introducing hybrid relay nodes to transmit energy to passive terminals and forward terminal information, the distance between passive terminals and final receiving nodes of information is reduced, and the contradiction between passive terminals’ data transmission requirements and “double path loss” of radio frequency energy transmission in WPSN is alleviated. At the same time, in the relay-powered WPSN, the life span of the relay node is equal to the life span of the whole network. This paper studies the energy efficiency transmission scheme of the relay node to maximize the energy utilization efficiency of the relay node and improve the life span of the WPSN.

Swarm energy efficient power efficient gathering in sensor information systems protocol in wireless sensor networks

Wireless sensor network (WSN) is a network, which has more numbers of sensors that are small in nature and are self organised. The inbuilt battery system is provided in the sensor nodes through which the nodes can communicate and do good operations among the other nodes available in the network. Lifetime is the most essential parameter which needs to be maximised for the WSN. This measure is more important for conservation of energy, for adequate and efficient performance of sensor networks. This paper proposes a swarm energy efficient power efficient gathering in sensor information systems (PEGASIS) (SEE-PEG) based energy optimization algorithm for WSN in which clustering and clustering head selection are done by using modified particle swarm optimization (MPSO) algorithm with respect to minimizing the consumption of power in WSN. The parameters evaluated for the proposed method is compared with existing technique like energy efficient PEGASIS without optimization. The simulation results are obtained using matlab tool.

Research on data fusion of power wireless sensor networks based on Kalman filter

In order to overcome the problems existing in traditional methods such as large mean error and long time of network data fusion, a data fusion of power wireless sensor networks based on Kalman filter is proposed. Firstly, the composition of power wireless sensor is analyzed, and the data of power wireless sensor network is preprocessed. Then, the data fusion process of Kalman filter is designed, and the schematic diagram of the data fusion process is given. Finally, l-M method is used to modify the network data fusion prediction covariance matrix to realize the power wireless sensor network data fusion. Experimental results show that when the amount of data is 600 GB, the data fusion time of the proposed method is 1.89 s. When the number of Kalman recursion is 120, the mean square error of data fusion of the proposed method is 0.04, and the practical application effect is good.

Solar Powered Wireless Sensor Network for Water Quality Monitoring and Classification

Water is essential for human being, also for animals and plants. In Indonesia, there are a lot of residential living in the riverbank which have poor water conditions. People frequenty use water from the river for daily activities. To determine the quality of water, samples are usually taken and tested in the laboratory. This method is less efficient in time and also cost. In order to determine and monitor the quality of water, this paper discuss the Wireless Sensor Network (WSN) to monitor the quality of water from a distance with the self powered sensor node. One of the issue in developing the WSN is the energy. Since this is implemented in outdoor, therefore it is possible to use solar panel to produce the energy. In this study three indicators; pH, TDS, and turbidity; were used to determine water quality based on the Indonesian Minister of Health Regulation. The results examine the WSN performance, and also the analysys of the solar energy supply for each sensor node. The WSN successfully works in detect and clasify tha water quality category and display it in the monitoring center or user. The sensors are calibrated and works with tolerable error of sensor reading of 5,1%. The WSN node is embedded with solar panel to supply the energy for node component. Therefore it able to extend the lifetime of the networks devices with renewable energy to implement the Green WSN.

Modulation Configurations of Phase Locked Loops for High-Speed and High-Precision Wired and Wireless Applications

This paper summarizes the modulation configurations of phase locked loops (PLLs) and their integration in semiconductor circuits, e.g., the input modulation for cellular phones, direct-modulation for low power wireless sensor networks, feedback-loop modulation for high-speed transmission, and two-point modulation for short-range radio transceivers. In this survey, basic configuration examples of integrated circuits for wired and wireless applications which are using the PLL modulation configurations are explained. It is important to select the method for simply and effectively determining the characteristics corresponding to the specific application. The paper also surveys technologies for future PLL design for digitizing of an entire PLL to reduce the phase noise due to a modulation by using a feedback loop with a precise digital phase comparison and a numerically controlled oscillator with high linearity.

An L-shaped and bending-torsion coupled beam for self-adaptive vibration energy harvesting

Vibration energy harvesting is promising for powering wireless sensor networks for mechanical equipment monitoring. Considering the broadband feature of ambient vibrations, a novel L-shaped self-adaptive piezoelectric energy harvester (LSA-PEH) with a slider is proposed. A linearized mathematical model of the LSA-PEH is established to obtain the relationship between its resonant frequency and the slider position. The maximum resonant frequency that can be achieved by the LSA-PEH is predicted based on the linearized model. The corresponding condition is to fix the slider at around 0.08 m, which is a nodal point. Moreover, the theoretical model explains why the slider moves back and forth when the excitation frequency is 40 Hz. Experimental results show that the slider of the proposed LSA-PEH can passively relocate its position to adjust its resonant frequency and maintain resonance. By the same criteria, the bandwidth of the proposed LSA-PEH is increased by 350% compared to a conventional L-shaped beam harvester.

A sustainable energy strategy powered wireless sensor network system for monitoring child safety

Children's safety education and environmental monitoring are the stability of a family and the foundation of a country's future development. Therefore, the safety of young children is never an independent problem in any aspect, nor is it a problem solved afterwards, but a long-term problem with monitoring effect. We need to use all accurate information to prevent potential safety hazards in advance and protect the healthy growth of children. In addition to using school resources to carry out health education for children, parents and society can also take precautions. The place environment of the kindergarten is a security system with an internal structure, from the equipment in the kindergarten to the dynamic monitoring. Many countries use sensor networks to achieve security monitoring in various fields. We can also use similar methods in terms of child safety. This paper constructs a system model based on sustainable energy strategy powered wireless sensor network system, and optimizes it to adapt to the safety monitoring system of children's external environment. First of all, based on child safety management and environmental education, this paper uses literature survey, questionnaire survey and other methods to study the current situation of attention to child safety in various countries. With this topic as the background, summarize the main problems faced by children's safety, and propose targeted solutions. According to the children's monitoring system, wireless sensor networks are used to build the monitoring system, and sustainable energy is used as the optimization mechanism of sensors. Finally, the sustainable Energy Strategy Powered Wireless Sensor Network System is applied to the children's environment system, and real-time data collection and remote monitoring are used to view children's activity information. Research shows that sustainable energy provides the endurance of wireless sensor safety monitoring system. This child safety monitoring system can be used in any environment and conditions, and has achieved good results.

Frequency‐tunable resonant hybrid vibration energy harvester using a piezoelectric cantilever with electret‐based electrostatic coupling

AbstractHybrid vibration energy harvesting technology converts vibration energy into electricity using multiple transduction mechanisms to improve output power. A frequency‐tunable resonant hybrid vibration energy harvester using a piezoelectric cantilever with electret‐based electrostatic coupling is proposed in this article. The electrostatic coupling including electrostatic force coupling and electrical damping coupling is introduced by an electret film placed below the cantilever, where the electrostatic force acting on the cantilever realises a tunable resonant frequency and additional electrical damping boosts power output. A coupling electromechanical model is derived using Euler–Bernoulli beam theory and Kirchhoff's law. By investigating the static and dynamic stability of cantilever, the maximum electret surface potential is defined to prevent the pull‐in phenomenon. The damping of the device is evaluated, and the optimal electret surface potential is determined to obtain the matching of the electrical and mechanical damping for maximum power output. The resonant frequency of hybrid vibration energy harvester can be adjusted in range of 176.1 rad/s by changing the electret surface potential and resistive load. The experimental output power of hybrid vibration energy harvester was 5.2 μW, 27.4 times higher than that of the individual piezoelectric generator. The proposed hybrid vibration energy harvester exhibits a promising potential to power microelectronic devices and wireless sensor network node.

Joint Distributed Beamforming and Backscattering for UAV-Assisted WPSNs

This paper studies an unmanned aerial vehicle (UAV)-assisted wireless powered sensor network (WPSN), where sensor nodes of multiple types can simultaneously harvest radio-frequency energy from the UAV and then transmit sensing data by using harvested energy. A joint distributed beamforming (DBF) and backscattering scheme is designed, in which the sensor nodes of one type can perform DBF while the sensor nodes of other types perform distributed backscattering (DBS) to improve the received signal strength. A sum-throughput maximization problem is formulated by jointly optimizing DBF phases, DBS phases, and time allocation (TA), subject to the received signal-to-noise ratio constraints. Since the formulated problem is difficult to be solved due to the tightly coupled optimizing variables, the problem is decoupled into a TA subproblem and a phase optimization subproblem, and then a two-step algorithm is proposed to solve them. Firstly, the closed-form solution for the TA subproblem is derived according to Karush-Kuhn-Tucker conditions. Secondly, based on iterative optimization and one-dimensional search methods, a centralized algorithm is proposed to obtain the optimal solution for the phase optimization subproblem. Moreover, a decentralized algorithm that obtains the suboptimal solution is proposed to reduce the computational complexity. Extensive simulation results validate the effectiveness of the proposed scheme on throughput enhancement.

Joint Optimization of Altitude and Beamwidth for UAV-Powered Wireless Sensor Networks

In this paper, we consider an unmanned aerial vehicle (UAV)-powered wireless sensor network (WSN) in which a UAV transfers wireless energy to ground sensor (GS) nodes using a directional antenna, and the GS nodes use the harvested energy to transmit sensing information back to the UAV. Considering the tradeoff aspect in adjusting the antenna beamwidth and altitude of the UAV, we jointly optimize the altitude and beamwidth to collect sensing data from all GSs as quickly as possible. The numerical analysis verifies the existence of unique altitude and beamwidth values that minimize the data collection time. The simulation result indicates that the use of a directional antenna and the joint optimization of altitude and beamwidth are essential for maximizing the performance of UAV-powered WSN systems.

ARCH: Adaptive Resource Allocation for Cooperative Transmission in Hybrid SWIPT-Enabled Wireless Powered Sensor Networks

ARCH: Adaptive Resource Allocation for Cooperative Transmission in Hybrid SWIPT-Enabled Wireless Powered Sensor Networks

Energy-Efficient Routing Protocol with Multi-Hop Fuzzy Logic for Wireless Networks

A Wireless Sensor Network (WSN) becomes a newer type of real-time embedded device that can be utilized for a wide range of applications that make regular networking which appears impracticable. Concerning the energy production of the nodes, WSN has major issues that may influence the stability of the system. As a result, constructing WSN requires devising protocols and standards that make the most use of constrained capacity, especially the energy resources. WSN faces some issues with increased power utilization and an on going development due to the uneven energy usage between the nodes. Clustering has proven to be a more effective strategy in this series. In the proposed work, a hybrid method is used for reducing the energy consumption among CHs. A Fuzzy Logic-based clustering protocol FLUC (unequally clustered) and Fuzzy Clustering with Energy-Efficient Routing Protocol (FCERP) are used. A Fuzzy Clustering with Energy Efficient Routing Protocol (FCERP) reduces the WSN power usage and increases the lifespan of the network. FCERP has created a novel cluster-based fuzzy routing mechanism that uses a limit value to combine the clustering and multi-hop routing capabilities. The technique creates uneven groups by using fuzzy logic with a competitive range to choose the Cluster Head (CH). The input variables include the distance of the nodes from the ground station, concentrations, and remaining energy. The proposed FLUC-FCERP reduces the power usage and improves the lifetime of the network compared with the existing algorithms.

Transmit Power Control for Secure Wireless-Powered Sensor Networks With Malicious Energy Harvester

Transmit Power Control for Secure Wireless-Powered Sensor Networks With Malicious Energy Harvester

6WPSN: Reliable and efficient IPv6 packet broadcast protocol for IEEE 802.15.4-based wireless powered sensor networks

6WPSN: Reliable and efficient IPv6 packet broadcast protocol for IEEE 802.15.4-based wireless powered sensor networks

Novel Network Structure and its Clustering Scheme Based on Residual Power for Wireless Powered Wireless Sensor Networks

Novel Network Structure and its Clustering Scheme Based on Residual Power for Wireless Powered Wireless Sensor Networks