Power Wireless Sensor Networks Research Articles

A Novel Design to Increase the Power Output of an Electromagnetic Vibration Energy Harvester Using Finite Element Analysis

The concept of Internet of Things has prompted the need for a sustainable energy source to power wireless sensor networks. Vibration energy harvesting emerges as an applicable option. This paper presents a finite element analysis of a new electromagnetic vibration energy harvester design aimed to increase the power output of an electromagnetic vibration energy harvester by making the coil and a pair of magnets vibrate in the opposite direction, hence increasing the speed of the coil cutting through the magnetic flux of the magnets. The design consist of a regular cantilever beam And one uniquely shaped cantilever beam designed to move in the opposite direction to the regular beam under the same base excitation. Results show that due to the opposite motion, the speed of the coil moving through the magnetic flux for the new design is equal to the sum of velocities from the two individual beams. This lead to a 99.3% increase in power output generated from the new design when compared with the sum of the individual power outputs produced by the two beams. Further analysis demonstrates that the maximum power decreases if a time lag was introduced between the two beams, hence stating the importance of matching their natural frequencies.

BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking.

In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible.

A Novel Hierarchical Two-Tier Node Deployment Strategy for Sustainable Wireless Sensor Networks

Wireless sensor networks (WSNs) have been widely adopted to fulfil the imperative requirement of real-time monitoring and/or long-term surveillance of the field-of-interest. However, due to the limited battery capacity, energy is the most critical constraint for improving the sustainability of a WSN. Hence, conserving energy and extending battery life are important in designing a sustainable WSN. Fortunately, the emerging energy harvest techniques provide us with a semi-permanent energy resource to power WSNs. In this article, we introduce a novel energy-aware hierarchical two-tier (HTT) energy harvesting-aided WSNs deployment scenario. More precisely, we consider two types of nodes in the system: one is the regular battery-powered sensor node (RSN), and the other is the energy harvesting-aided data relaying node (EHN). The objective is to use only RSNs to monitor FoI, while EHNs focus on collecting the sensed data from RSNs and forwarding the gathered data to the data sink. The minimum number of EHNs is deployed based on a newly designed probability density function to minimize the energy consumption of RSNs. This, in turn, extends the lifetime of the deployed WSN. The simulation results indicate that the proposed scheme outperforms some well-known techniques in the network lifetime, while enhancing the total throughput.

Designing prefix code to save energy for wirelessly powered wireless sensor networks

In the Internet of Things, wireless sensor networks (WSNs) are widely deployed. In recent years, wirelessly powered WSNs or battery-free WSNs (BF-WSNs), in which the nodes harvest energy from radio signals in the environment, have been emerging to support sustainable operation for WSNs. It is significant to design an energy-efficient data delivery scheme for the BF-WSNs. In this study, the authors propose the prefix code based scheme (PCBS) to save energy in data delivery by making use of the energy consumption disparity (ECD) between transmitting/receiving bit 0 and bit 1 in the existing non-modulation baseband transmission or carrier-modulation based passband transmission. The authors formulate an optimisation problem and use genetic algorithm to find its solution so that the energy-efficient prefix codebook is obtained. The codebook dilutes the ECD by containing the energy-consuming bit as few as possible, and the PCBS maps each m-bit data block into a prefix codeword in the codebook to conduct energy-efficient transmission at the transmitter and vice versa at the receiver. Both the experiments on wireless identification sensing platform and the simulations demonstrate that the proposed PCBS outperforms the existing schemes in terms of energy saving.

The Building low power wireless sensor network with TCP/IP for agriculture

This paper presents a low cost Wireless Sensor Network using TCP/IP to use Ethernet configuration and hybrid networks to extend range or improve connectivity in distant areas, in particular is agriculture. The system is designed with soil moisture sensor based on Atmega8L and Nordic nRF24L01 to monitor environmental parameter. Moreover, to make data available globally, we have connected the wireless sensor network to GSM/GPRS. The system not only uses a low power but also has a compact size and applies advantages of TCP/IP

Joint Transceiver Designs for MSE Minimization in MIMO Wireless Powered Sensor Networks

In this paper, we study vector parameter estimation in multiple-input multiple-output wireless-powered sensor networks (WPSNs) where sensor nodes operate by harvesting the radio frequency signals transmitted from energy access points (E-APs). We investigate a joint design of sensor data precoders, a fusion rule, and energy covariance matrices to minimize the mean square error (MSE) of the parameter estimate based on a non-linear energy harvesting model. First, we propose a centralized algorithm to solve the MSE minimization problem. Next, to reduce the computational complexity at the fusion center (FC) and feedback overhead from the sensors to the FC, we present a distributed algorithm to locally compute the precoders and the energy covariance matrices. We employ the alternating direction method of multipliers technique to minimize the MSE in a distributed manner without any coordination from the FC. In the proposed distributed algorithm, each sensor node calculates its own precoders and determines the local information of the fusion rule, and then messages are broadcast to other sensor nodes and E-APs. Simulation results demonstrate that the distributed algorithm performs close to the centralized algorithm with reduced complexity. Moreover, the proposed methods exhibit superior estimation performance over conventional techniques in WPSNs.

Optimal Beamforming and Time Allocation for Partially Wireless Powered Sensor Networks With Downlink SWIPT

Wireless powered sensor networks (WPSNs) have emerged as a key development towards the future self-sustainable Internet of Things (IoT) networks. To achieve a good balance between self-sustainability and reliability, partially WPSNs with a mixed power solution are desirable for practical applications. Specifically, most of the sensor nodes are wireless powered but the key sensor node adopts traditional wire/battery power for reliability. As a result, this paper mainly investigates optimal design for the partially WPSNs in which simultaneous wireless information and power transfer (SWIPT) is adopted in the downlink. Two scenarios with space division multiple access (SDMA) and time division multiple access (TDMA) in the uplink are considered. For both the SDMA-enabled and TDMA-enabled partially WPSNs, joint design of downlink beamforming, uplink beamforming and time allocation is investigated to maximize the uplink sum rate while guaranteeing the quality-of-service (i.e., satisfying the downlink rate constraint) at the key sensor node. After analyzing the feasibility of uplink sum rate maximization problems and the influence of the downlink rate constraint, semi-closed-form optimal solutions for both SDMA-enabled and TDMA-enabled WPSNs are proposed with guaranteed global optimality. Complexity analysis is also provided to justify the advantage of the proposed solutions in low complexity. The effectiveness and optimality of the proposed optimal solutions are finally demonstrated by simulations.

Connectivity Analysis in Clustered Wireless Sensor Networks Powered by Solar Energy

Emerging 5G communication paradigms, such as machine-type communication, have triggered an explosion in ad-hoc applications that require connectivity among the nodes of wireless networks. Ensuring a reliable network operation under fading conditions is not straightforward, as the transmission schemes and the network topology, i.e., uniform or clustered deployments, affect the performance and should be taken into account. Moreover, as the number of nodes increases, exploiting natural energy sources and wireless energy harvesting (WEH) could be the key to the elimination of maintenance costs while also boosting immensely the network lifetime. In this way, zero-energy wireless-powered sensor networks (WPSNs) could be achieved, if all components are powered by green sources. Hence, designing accurate mathematical models that capture the network behavior under these circumstances is necessary to provide a deeper comprehension of such networks. In this paper, we provide an analytical model for the connectivity in a large-scale zero-energy clustered WPSN under two common transmission schemes, namely, unicast and broadcast. The sensors are WEH-enabled, while the network components are solar-powered and employ a novel energy allocation algorithm. In our results, we evaluate the tradeoffs among the various scenarios via extensive simulations and identify the conditions that yield a fully connected zero-energy WPSN.

IoT based reconfigurable smart city architecture

Now-a-days Internet of Things is deployed almost in every application regarding smart cities and have been initiated to develop all over the world. Smart Devices are being geared up to ease human life. Due to the growth in Internet of Things technology, smart cities are been developedwith this technology to work with the issues of public as well as private. The aim of the article is to enhance a solution to the problems in the smart cities with latest IoT architecture, protocols and services. With the technical support of IoT, using low power Wireless Sensor Networks (WSN) which is connected to transfer the data from M2M applications. In addition to the IoT, intelligent features are integrated with the help of Computer vision makes the technology more flexible. The goal of this article is to engrave the services to challenge the real time environment with low power synthesis technique. Only then, the smart city features are improved and serves the mankind with IoT technology.

Medium and Short Wave RF Energy Harvester for Powering Wireless Sensor Networks.

Internet of Things (IoT) is an emerging platform in which every day physical objects provided with unique identifiers are connected to the Internet without requiring human interaction. The possibilities of such a connected world enables new forms of automation to make our lives easier and safer. Evidently, in order to keep billions of these communicating devices powered long-term, a self-sustainable operation is a key point for realization of such a complex network. In this sense, energy-harvesting technologies combined with low power consumption ICs eliminate the need for batteries, removing an obstacle to the success of the IoT. In this work, a Radio Frequency (RF) energy harvester tuned at AM broadcast has been developed for low consumption power devices. The AM signals from ambient are detected via a high-performance antenna-free LC circuit with an efficiency of 3.2%. To maximize energy scavenging, the RF-DC conversion stage is based on a full-wave Cockcroft–Walton voltage multiplier (CWVM) with efficiency up to 90%. System performance is evaluated by rating the maximum power delivered into the load via its output impedance, which is around 62 μW, although power level seems to be low, it is able to power up low consumption devices such as Leds, portable calculators and weather monitoring stations.

Energy Efficiency Optimization For Wireless Powered Sensor Networks With Nonorthogonal Multiple Access

This article studies a wireless powered sensor network (WPSN), where sensors harvest energy from a hybrid access point (H-AP) and then transmit information to the H-AP via nonorthogonal multiple access (NOMA) scheme. The energy efficiency (EE) maximization problem for the NOMA-based WPSN is, for the first time, formulated as a nonlinear fractional programming, which is difficult to solve for global optimality due to the lack of convexity. To this end, we propose two important properties for the optimal solution to the EE maximization problem, based on which a particle-swarm-optimization-based solution algorithm is proposed. Simulations demonstrate the fast convergence and stability of the proposed algorithm.

Wireless Powered Sensor Networks for Internet of Things: Maximum Throughput and Optimal Power Allocation

This paper investigates a wireless powered sensor network, where multiple sensor nodes are deployed to monitor a certain external environment. A multiantenna power station (PS) provides the power to these sensor nodes during wireless energy transfer phase, and consequently the sensor nodes employ the harvested energy to transmit their own monitoring information to a fusion center during wireless information transfer (WIT) phase. The goal is to maximize the system sum throughput of the sensor network, where two different scenarios are considered, i.e., PS and the sensor nodes belong to the same or different service operator(s). For the first scenario, we propose a global optimal solution to jointly design the energy beamforming and time allocation. We further develop a closed-form solution for the proposed sum throughput maximization. For the second scenario in which the PS and the sensor nodes belong to different service operators, energy incentives are required for the PS to assist the sensor network. Specifically, the sensor network needs to pay in order to purchase the energy services released from the PS to support WIT. In this case, this paper exploits this hierarchical energy interaction, which is known as energy trading. We propose a quadratic energy trading-based Stackelberg game, linear energy trading-based Stackelberg game, and social welfare scheme, in which we derive the Stackelberg equilibrium for the formulated games, and the optimal solution for the social welfare scheme. Finally, numerical results are provided to validate the performance of our proposed schemes.

A Compact and Low Power RO PUF with High Resilience to the EM Side-Channel Attack and the SVM Modelling Attack of Wireless Sensor Networks.

Authentication is a crucial security service for the wireless sensor networks (WSNs) in versatile domains. The deployment of WSN devices in the untrusted open environment and the resource-constrained nature make the on-chip authentication an open challenge. The strong physical unclonable function (PUF) came in handy as light-weight authentication security primitive. In this paper, we present the first ring oscillator (RO) based strong physical unclonable function (PUF) with high resilience to both the electromagnetic (EM) side-channel attack and the support vector machine (SVM) modelling attack. By employing an RO based PUF architecture with the current starved inverter as the delay cell, the oscillation power is significantly reduced to minimize the emitted EM signal, leading to greatly enhanced immunity to the EM side-channel analysis attack. In addition, featuring superior reconfigurability due to the conspicuously simplified circuitries, the proposed implementation is capable of withstanding the SVM modelling attack by generating and comparing a large number of RO frequency pairs. The reported experimental results validate the prototype of a 9-stage RO PUF fabricated using standard 65 nm complementary-metal-oxide-semiconductor (CMOS) process. Operating at the supply voltage of 1.2 V and the frequency of 100 KHz, the fabricated RO PUF occupies a compact silicon area of 250 m and consumes a power as low as 5.16 W per challenge-response pair (CRP). Furthermore, the uniqueness and the worst-case reliability are measured to be 50.17% and 98.30% for the working temperature range of −40∼120 C and the supply voltage variation of ±2%, respectively. Thus, the proposed PUF is applicable for the low power, low cost and secure WSN communications.

Modeling and preliminary analysis of piezoelectric energy harvester based on cylindrical tube conveying fluctuating fluid

In this contribution, a novel type of piezoelectric tubular energy harvester based on fluctuating fluid pressure is investigated. Analytic model of the proposed energy harvester is built under the assumption of axisymmetric radial vibration. Exact solution of the piezoelectric vibrating tube is obtained with its output performances formulated. A series of numerical simulations are conducted to investigate the influences of geometrical parameters, input mechanical load parameters and output electrical load parameters upon the output performances of the proposed piezoelectric tubular energy harvester. The model and simulation results indicate the potential of the proposed piezoelectric tubular energy harvester. It is expected that the energy harvester be useful in powering wireless sensor network for the health monitoring of hydraulic systems, where fluid conveying pipe vibration is omnipresent.

HE-MAC: Harvest-Then-Transmit Based Modified EDCF MAC Protocol for Wireless Powered Sensor Networks

Energy transfer (ET) and energy harvesting (EH) through radio frequency (RF) signals are a promising technology that can reduce the dependency on batteries in wireless sensor networks. However, there is a tradeoff between the RF-based ET and data communication when they operate in the same frequency band. Therefore, a proper medium access control (MAC) protocol is needed in wireless powered sensor networks (WPSNs). However, a utilization degradation problem occurs when the distributed coordination function (DCF) MAC protocol of the IEEE 802.11 is applied to WPSNs. In order to overcome this problem, this paper extends the IEEE 802.11e enhanced DCF (EDCF) into a harvest-then-transmit-based modified EDCF MAC (HE-MAC) protocol. In addition, the HE-MAC’s Markov chain model and steady-state probabilities are derived and used in the performance analysis. Next, based on the steady-state conditions, optimization is conducted to maximize the EH rate, which satisfies the frame generation rate and transfers additional energy to achieve a self-sustained energy consumption profile. Finally, the simulation performance of EH protocols HE-MAC, RF-MAC, and DOS are compared, where the results show that HE-MAC provides in a superior performance for the range of interest.

Theory and Experiment for Wireless-Powered Sensor Networks: How to Keep Sensors Alive

In this paper, we investigate a multi-node multi-antenna wireless-powered sensor network (WPSN) comprised of one power beacon and multiple sensor nodes. We have implemented a real-life multi-node multi-antenna WPSN testbed that operates in real time. We propose a beam-splitting beamforming technique that enables a power beacon to split microwave energy beams toward multiple nodes for simultaneous charging. We experimentally demonstrate that the beam-splitting beamforming technique achieves the Pareto optimality. For perpetual operation of the sensor nodes, we adapt an energy neutral control algorithm that keeps a sensor node alive by balancing the harvested and consumed power. The joint beam-splitting and energy neutral control algorithm is designed by means of the Lyapunov optimization technique. In our experiments, the proposed algorithm has successfully kept all sensor nodes alive by optimally splitting energy beams toward multiple sensor nodes.

Study of Mobility Enhancements for RPL in Convergecast Scenarios

In recent years, mobility support has become an important requirement in various wireless sensor network (WSN) applications. However, due to the strict resource constraints of power, memory, and processing resources in WSNs, routing protocols are mainly designed without considering mobility. Low-Power and Lossy Networks (LLNs) are a special type of WSNs that tolerate data loss. The Routing Protocol for Low-Power and Lossy Networks (RPL) is a routing protocol for LLNs that adapts IPv6 (Internet Protocol version 6) and runs on top of the IEEE (Institute of Electrical and Electronics Engineers) 802.15.4 standard. RPL supports multipoint-to-point traffic and point-to-multipoint traffic. In this paper we propose a mobility enhancement mechanism in order to improve data collection applications in highly mobile scenarios. The enhancement is based on signal strength monitoring and depth updating in order to improve the routing protocol performance in mobile scenarios. This enhancement helps routing protocols to cope better with topology changes and makes proactive decisions on updating next-hop neighbours. We integrated this mechanism into the RPL and compared it with other existing RPL mobility support enhancements. Results obtained through simulation using Cooja show that our work outperforms other existing RPL mobility supports on different performance metrics. Results also prove the efficiency of our proposal in highly mobile scenarios.

무선 전력 전송 센서 네트워크에서 다중 접속에 따른 정보 및 전력 전송 기법 연구

무선 전력 전송 센서 네트워크에서 다중 접속에 따른 정보 및 전력 전송 기법 연구

A Study on Piezoelectric Energy-Harvesting Wireless Sensor Networks Deployed in a Weak Vibration Environment

Wireless sensor network (WSN) is an interestingly promising technology with many applications in intelligent environment-monitoring. Its energy consumption is, however, essentially challenged after it is deployed. In this paper, we developed a low-resonant-frequency piezoelectric energy harvesting device as an alternative to power WSN deployed in a weak vibration environment. An energy management module, equipped with a full-bridge rectifier (FBR), a fully self-powered voltage controller, and a logic-level protection circuit was designed to enable a regulated voltage to intermittently drive WSN for temperature monitoring. The power transfer efficiency of FBR reached 42%, presenting a good performance/cost ratio in the case of a relatively high open-circuit voltage of 8 V and a low rectified voltage of 3.3 V. The experimental results have demonstrated that the proposed WSN was successfully driven at an interval time of less than 1 min, and fully self-powered by the scavenged energy from the environmental vibration source of a 0.15-g acceleration and a 40-Hz vibration frequency.

Operation strategy for wireless‐powered heterogeneous sensor networks

A wireless-powered heterogeneous sensor network is considered whose sensor nodes (SNs) harvest energy from a radio signal emitted from a base node (BN) communicating with user nodes and then transmit the collected information to a data collection node. In order to maximise the throughput of the sensor network under the interference limit on the BNs, an algorithm that optimises the duration of the phases and the transmit power of the SNs is proposed. By comparing to a method with a fixed time ratio for energy harvesting, the benefit of the proposed method is verified.