scholarly journals A Novel Charging Method for Underwater Batteryless Sensor Node Networks

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 557
Author(s):  
Judith Santana Abril ◽  
Graciela Santana Sosa ◽  
Javier Sosa ◽  
Tomas Bautista ◽  
Juan A. Montiel-Nelson

In this paper, we present a novel charging method for underwater batteryless sensor node networks. The target application is a practical underwater sensor network for oceanic fish farms. The underwater sections of the network use a wireless power transfer system based on the ISO 11784/11785 HDX standard for supplying energy to the batteryless sensor nodes. Each sensor has an accumulator capacitor, which is charged for voltage supplying to the sensor node. A new distributed charging scheme is proposed and discussed in detail to reduce the required time to charge all sensor nodes of the underwater sections. One important key is its decentralized control of the charging process. The proposal is based on the self disconnection ability of each sensor node from the charging network. The second important key is that the hardware implementation of this new feature is quite simple and only requires to include a minimal circuitry in parallel to the current sensor node antenna while the rest of the sensor network remains unaltered. The proposed charging scheme is evaluated using real corner cases from practical oceanic fish farms sensor networks. The results from experiments demonstrate that it is possible to charge up to 10 sensor nodes which is the double charging capability than previous research presented. In the same conditions as the approach found in the literature, it represents reaching an ocean depth of 60 m. In terms of energy, in case of an underwater network with 5 sensors to reach 30 m deep, the proposed charging scheme requires only a 25% of the power required using the traditional approach.

Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.


2013 ◽  
Vol 347-350 ◽  
pp. 1920-1923
Author(s):  
Yu Jia Sun ◽  
Xiao Ming Wang ◽  
Fang Xiu Jia ◽  
Ji Yan Yu

The characteristics and the design factors of wireless sensor network node are talked in this article. According to the design factors of wireless sensor network, this article will mainly point out the design of wireless sensor nodes based a Cortex-M3 Microcontroller STM32F103RE chip. And the wireless communication module is designed with a CC2430 chip. Our wireless sensor node has good performance in our test.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 95878-95887
Author(s):  
Bilal Tariq Malik ◽  
Viktor Doychinov ◽  
Ali Mohammad Hayajneh ◽  
Syed Ali Raza Zaidi ◽  
Ian D. Robertson ◽  
...  

Author(s):  
Monjul Saikia

The wireless sensor network is a collection of sensor nodes that operate collectively to gather sensitive data from a target area. In the process of data collection the location of sensor nodes from where data is originated matters for taking any decision at the base station. Location i.e. the coordinates of a sensor node need to be shared among other nodes in many circumstances such as in key distribution phase, during routing of packets and many more. Secrecy of the location of every sensor node is important in any such cases. Therefore, there must be a location sharing scheme that facilitates the sharing of location among sensor nodes securely. In this paper, we have proposed a novel secure and robust mechanism for location sharing scheme using 2-threshold secret sharing scheme. The implementation process of the proposed model is shown here along with results and analysis.


Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 639 ◽  
Author(s):  
Ahmad Ali ◽  
Yu Ming ◽  
Sagnik Chakraborty ◽  
Saima Iram ◽  
Tapas Si

Present research in the domain of wireless sensor network (WSN) has unearthed that energy restraint of sensor nodes (SNs) encumbers their perpetual performance. Of late, the encroachment in the vicinity of wireless power transfer (WPT) technology has achieved pervasive consideration from both industry and academia to cater the sensor nodes (SNs) letdown in the wireless rechargeable sensor network (WRSNs). The fundamental notion of wireless power transfer is to replenish the energy of sensor nodes using a single or multiple wireless charging devices (WCDs). Herein, we present a jointly optimization model to maximize the charging efficiency and routing restraint of the wireless charging device (WCD). At the outset, we intend an unswerving charging path algorithm to compute the charging path of the wireless charging device. Moreover, Particle swarm optimization (PSO) algorithm has designed with the aid of a virtual clustering technique during the routing process to equilibrate the network lifetime. Herein clustering algorithm, the enduring energy of the sensor nodes is an indispensable parameter meant for the assortment of cluster head (CH). Furthermore, compare the proposed approach to corroborate its pre-eminence over the benchmark algorithm in diverse scenarios. The simulation results divulge that the proposed work is enhanced concerning the network lifetime, charging performance and the enduring energy of the sensor nodes.


2013 ◽  
Vol 756-759 ◽  
pp. 746-750
Author(s):  
Dong Rong Wu ◽  
He Jun Wu ◽  
Xiao Lu Zhu

Power shortage is one of critical issues stalling the development of wireless sensor networks. This paper attempts to address this issue by means of microwave power transmission. In this paper, we propose a sensor node framework using a high-frequency microwave power transmitting module to allow sensor nodes to transmit power to others. We introduce the process of exchanging power between two adjacent sensor nodes and design a power transmission routing protocol called PTR in this paper. PTR optimizes the power transmission of a whole network so that the power of energy sources can efficiently reach any sensor node in the network. We have done simulations and analysis on this framework and the results are positive.


2020 ◽  
Author(s):  
Yang Wang ◽  
feifan wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao

Abstract In wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an Improved Cuckoo Search (ICS) algorithm is proposed. This algorithm is based on the traditional Cuckoo Search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird ’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.


2021 ◽  
Vol 6 (7) ◽  
pp. 169-172
Author(s):  
Emmanuel M. Eronu ◽  
Matthew O. Oboh ◽  
Emeka S. Ezeh ◽  
Gafar Tiamiyu ◽  
Farouq E. Shaibu

Electrical Energy crisis is a major problem faced in the world today and it’s increasingly significant in this part of Africa. A perfect solution seems not to be feasible as several solutions have been proposed in the past by various authors with little impact on the power sector. In this work, we present a method of Non-Technical Loss (NTL) detection consisting of a microcontroller interfaced with a current sensor that measures the current on the power line. A sensor node is placed at the supply end of the pole while two or more others sensor nodes are connected to the output of the pole depending on the number of consumers. The measured value of current is sent via the microcontroller to a web cloud that is accessible by the consumers and the utility company from any part of the world by simply logging on to the website; www.electricity-theft.herokuapp.com. The design uses the principle of Kirchhoff Current Law (KCL) to achieve this aim. The consumers can therefore monitor their power consumption from any location in the world and prevent theft on the network. The results obtained from the installation of the sensor nodes were analyzed using correlation and regression analysis. A correlation analysis of the data results gave us a correlation coefficient of 0.9802, while a regression analysis provided us with a linear relationship between the dependent and independent variable expressed mathematically thus Y = 0.916x + 0.254. A regression graph is also plotted. Furthermore, a T-Test and F-Test was conducted to statistically test the sensor nodes. A NodeMCU Wi-Fi microcontroller and a self-powered Phidget current sensor is used for the sensor node design. Communication between the sensor nodes is via Wi-Fi while a 4G router was used to provide internet services.


2019 ◽  
Vol 16 (9) ◽  
pp. 3925-3931
Author(s):  
Bhupesh Gupta ◽  
Sanjeev Rana

For resource constraint network, one uses wireless sensor network in which limited resources are there for sensor nodes. Basic aim of sensor node is to sense something, monitor it and explain it. The issue arises for sensor node is its battery endurance. The battery endurance of sensor node is consuming in communication instead of sensing. In this regard clustering is using now a day’s which reduces endurance consumption. This paper comes with a new clustering protocol MESAEED (Mutual Exclusive Sleep Awake Energy Efficient Distributed clustering), which helps in saving endurance of sensor nodes so that network lifetime will prolong. It is an extension work of previous work MESADC. In previous work cluster head is chooses on the basis of sleep awake mode in mutual exclusive way under communication range and the results were obtained with the help of comparison graph between HEED and MESADC. The proposed MESAEED protocol provides benefit of A* algorithm of heuristic search, HEED and MESADC. MATLAB 8.3 is use for simulation purpose. The comparison graph between HEED, MESADC and proposed MESAEED were shown. Parameters for comparison include alive nodes versus number of rounds taken and number of nodes dead versus number of rounds taken. The graph shows improvement in performance over HEED and MESADC, which results in enhancing lifetime of WSN.


2013 ◽  
Vol 321-324 ◽  
pp. 515-522 ◽  
Author(s):  
Kou Lin Yuan ◽  
Lin Qiao ◽  
Lei Han

This paper proposes a level and cluster based routing approach for a wireless sensor network. Nodes in the network are divided into several levels according to their hops to sink node. Every sensor node has a level number. Using level information, a sensor node can send messages to a sink node in a more efficient way, and a sink node can easily locate other sensor nodes. To make network more balanced, the paper introduces a cluster method, which splits nodes in the same level into different clusters, and chooses a cluster head for every cluster, to switch nodes in the cluster to work in turn. Unlike all other cluster routing methods, a cluster head node takes schedule jobs of sensor nodes in the cluster according to their energy left, instead of sensing. The paper also presents several algorithms for constructing a wireless sensor network, querying and scheduling. The simulation experiment shows that the scalability of our method is approximately linear.


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