scholarly journals Underwater Wireless Sensor Networks

2018 ◽  
Vol 2 (1) ◽  
pp. 10
Author(s):  
Sweta S ◽  
Balajee Maram
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Autonomous Underwater Vehicle ◽  
Low Cost ◽  
Energy Resources ◽  
Sensor Nodes ◽  
Pollution Monitoring ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Underwater Acoustic

There are a plenty of unexploited resources that lies underwater that covers almost 75% of the earth.In order to utilise them,the field of underwater wireless sensor networks (UWSN) is attracting the  researchers to extend their thoughts in this field. The wireless sensor networks are heavy networks that consist of small low cost sensors that have a large amount of solving ability and energy resources which can be applicable in any type of irregular environments irrespective of changing conditions. Keeping in view of the real-time remote data transferring requirements, underwater acoustic sensor networks (UASN) has been recognised as a preferred network because it satisfies all aspects of data transfer. In UASN, the required availability and recycling of energy resources along with specified utilisation of data with the help of utilized sensor nodes for energy requirements that are necessary are done for the development of  further theories in these contexts. Due to these causes, the maximum underwater resources utilisation techniques mainly depends on UAN (Underwater Acoustic Networks).Underwater wireless sensor networks (UWSNs) suitable for applications on submarine detection and monitoring,where nodes collect data with a mobile autonomous underwater vehicle (AUV) via optical communications, and applied accordingly to deal with further approaches. They provide continuous monitoring for various applications like ocean sampling network, pollution monitoring, submarine detection, disaster prevention etc.This paper particularly deals with a brief collection of the UWSN applications and some of the algorithms for the path finding in order to pass  maximum valued information(VOI) among the different nodes.

scholarly journals A Localization Based Cooperative Routing Protocol for Underwater Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Nadeem Javaid ◽  
Hammad Maqsood ◽  
Abdul Wadood ◽  
Iftikhar Azim Niaz ◽  
Ahmad Almogren ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Autonomous Underwater Vehicle ◽  
Sensor Nodes ◽  
Maximal Ratio Combining ◽  
Wireless Sensor ◽  
Localization Error ◽  
Amplify And Forward ◽  
Underwater Wireless Sensor Networks

Localization is one of the major aspects in underwater wireless sensor networks (UWSNs). Therefore, it is important to know the accurate position of the sensor node in large scale applications like disaster prevention, tactical surveillance, and monitoring. Due to the inefficiency of the global positioning system (GPS) in UWSN, it is very difficult to localize a node in underwater environment compared to terrestrial networks. To minimize the localization error and enhance the localization coverage of the network, two routing protocols are proposed; the first one is mobile autonomous underwater vehicle (MobiL-AUV) and the second one is cooperative MobiL (CO-MobiL). In MobiL-AUV, AUVs are deployed and equipped with GPS and act as reference nodes. These reference nodes are used to localize all the nonlocalized ordinary sensor nodes in order to reduce the localization error and maximize the network coverage. CO-MobiL is presented in order to improve the network throughput by using the maximal ratio combining (MRC) as diversity technique which combines both signals, received from the source and received from the relay at the destination. It uses amplify-and-forward (AF) mechanism to improve the signal between the source and the destination. To support our claims, extensive simulations are performed.

scholarly journals An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1368 ◽  
Author(s):  
Luoheng Yan ◽  
Yuyao He ◽  
Zhongmin Huangfu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Balance ◽  
Optimization Algorithm ◽  
Growth Ring ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Connected Network ◽  
Deployment Optimization

The underwater wireless sensor networks (UWSNs) have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, however, it is a challenging problem due to the complex underwater environment. This paper proposes a growth ring style uneven node depth-adjustment self-deployment optimization algorithm (GRSUNDSOA) to improve the coverage and reliability of UWSNs, meanwhile, and to solve the problem of energy holes. In detail, a growth ring style-based scheme is proposed for constructing the connective tree structure of sensor nodes and a global optimal depth-adjustment algorithm with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance is proposed. Initially, the nodes are scattered to the water surface to form a connected network on this 2D plane. Then, starting from sink node, a growth ring style increment strategy is presented to organize the common nodes as tree structures and each root of subtree is determined. Meanwhile, with the goal of global maximizing coverage utilization and energy balance, all nodes depths are computed iteratively. Finally, all the nodes dive to the computed position once and a 3D underwater connected network with non-uniform distribution and balanced energy is constructed. A series of simulation experiments are performed. The simulation results show that the coverage and reliability of UWSN are improved greatly under the condition of full connectivity and energy balance, and the issue of energy hole can be avoided effectively. Therefore, GRSUNDSOA can prolong the lifetime of UWSN significantly.

scholarly journals Using Mobile Elements as Dynamic Bridges in Sparse Wireless Sensor Networks

2014 ◽  
pp. 107
Author(s):  
Hoang Dang Hai ◽  
Thorsten Strufe ◽  
Pham Thieu Nga ◽  
Hoang Hong Ngoc ◽  
Nguyen Anh Son ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Exchange ◽  
Data Transfer ◽  
Mobile Elements ◽  
Sensor Nodes ◽  
Pollution Monitoring ◽  
Wireless Sensor ◽  
Mobile Nodes ◽  
Road Distance

Sparse  Wireless  Sensor  Networks  using several  mobile  nodes  and  a  small  number  of  static sensor  nodes  have  been  widely  used  for  many applications,  especially  for  traffic-generated  pollution monitoring.  This  paper  proposes  a  method  for  data collection and forwarding using Mobile Elements (MEs), which are moving on predefined trajectories in contrast to previous works that use a mixture of MEsand static nodes. In our method, MEscan be used as data collector as well as dynamic bridges for data transfer. We design the  trajectories  in  such  a  way,  that  they  completely cover  the  deployed  area  and  data  will  be  gradually forwarded  from  outermost  trajectories  to  the  center whenever  a  pair  of MEs contacts  each  other  on  an overlapping road distance of respective trajectories. The method  is based  on  direction-oriented  level  and  weight assignment.  We  analyze  the  contact  opportunity  for data  exchange  while MEs move.  The  method  has  been successfully tested for traffic pollution monitoring in an urban area.

Basic Concepts of Wireless Sensor Networks

2011 ◽  
pp. 57-64
Author(s):  
Lina M. Pestana Leão de Brito ◽  
Laura M. Rodríguez Peralta
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Low Cost ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Sensor Networks ◽  
Distributed Sensor ◽  
Technological Advances ◽  
The Cost ◽  
Communication Equipment

As with many technologies, defense applications have been a driver for research in sensor networks, which started around 1980 due to two important programs of the Defense Advanced Research Projects Agency (DARPA): the distributed sensor networks (DSN) and the sensor information technology (SensIT) (Chong & Kumar, 2003). However, the development of sensor networks requires advances in several areas: sensing, communication, and computing. The explosive growth of the personal communications market has driven the cost of radio devices down and has increased the quality. At the same time, technological advances in wireless communications and electronic devices (such as low-cost, low-power, small, simple yet efficient wireless communication equipment) have enabled the manufacturing of sensor nodes and, consequently, the development of wireless sensor networks (WSNs).

A STATIC-LEACH WSNs for Hazardous Materials Monitoring

2012 ◽  
Vol 463-464 ◽  
pp. 261-265
Author(s):  
Fei Hui ◽  
Xiao Le Wang ◽  
Xin Shi
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Low Cost ◽  
Hazardous Materials ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hazardous Materials Transportation ◽  
Adaptive Clustering

In this paper, hazardous materials transportation monitoring system is designed, implemented, and tested using Wireless Sensor Networks (WSNs). According to energy consumption and response time during clustering of Wireless Sensor Networks LEACH (Low Energy Adaptive Clustering Hierarchy) routing protocol, we proposed STATIC-LEACH routing protocol based on static clustering, it can effectively reduce energy consumption of the wireless sensor nodes and reduce network latency of cluster. With WSN and GSM/GPRS, low cost and easy deployment remote monitoring is possible without interfering with the operation of the transportation.

scholarly journals An Energy-Aware Method for Selecting Cluster Heads in Wireless Sensor Networks

2020 ◽  
Vol 10 (21) ◽  
pp. 7886
Author(s):  
Atefeh Rahiminasab ◽  
Peyman Tirandazi ◽  
M. J. Ebadi ◽  
Ali Ahmadian ◽  
Mehdi Salimi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Base Station ◽  
Energy Resources ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Clustering ◽  
Clustering Protocol

Wireless sensor networks (WSNs) include several sensor nodes that have limited capabilities. The most critical restriction in WSNs is energy resources. Moreover, since each sensor node’s energy resources cannot be recharged or replaced, it is inevitable to propose various methods for managing the energy resources. Furthermore, this procedure increases the network lifetime. In wireless sensor networks, the cluster head has a significant impact on system global scalability, energy efficiency, and lifetime. Furthermore, the cluster head is most important in combining, aggregating, and transferring data that are received from other cluster nodes. One of the substantial challenges in a cluster-based network is to choose a suitable cluster head. In this paper, to select an appropriate cluster head, we first model this problem by using multi-factor decision-making according to the four factors, including energy, mobility, distance to centre, and the length of data queues. Then, we use the Cluster Splitting Process (CSP) algorithm and the Analytical Hierarchy Process (AHP) method in order to provide a new method to solve this problem. These four factors are examined in our proposed approach, and our method is compared with the Base station Controlled Dynamic Clustering Protocol (BCDCP) algorithm. The simulation results show the proposed method in improving the network lifetime has better performance than the base station controlled dynamic clustering protocol algorithm. In our proposed method, the energy reduction is almost 5% more than the BCDCP method, and the packet loss rate in our proposed method is almost 25% lower than in the BCDCP method.

scholarly journals A data forwarding algorithm based on Markov thought in underwater wireless sensor networks

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769198
Author(s):  
Dongwei Li ◽  
Jingli Du ◽  
Linfeng Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Success Rate ◽  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Bottom To Top

The underwater wireless sensor networks composed of sensor nodes are deployed underwater for monitoring and gathering submarine data. Since the underwater environment is usually unpredictable, making the nodes move or be damaged easily, such that there are several vital objectives in the data forwarding issue, such as the delivery success rate, the error rate, and the energy consumption. To this end, we propose a data forwarding algorithm based on Markov thought, which logically transforms the underwater three-dimensional deployment model into a two-dimensional model, and thus the nodes are considered to be hierarchically deployed. The data delivery is then achieved through a “bottom to top” forwarding mode, where the delivery success rate is improved and the energy consumption is reduced because the established paths are more stable, and the proposed algorithm is self-adaptive to the dynamic routing loads.

Energy Efficient Mobile Wireless Sensor Networks

Aerospace ◽  
2006 ◽  
Author(s):  
Shashank Priya ◽  
Dan Popa ◽  
Frank Lewis
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Low Cost ◽  
Electric Energy ◽  
Cmos Technology ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Total Power ◽  
Gas Temperature ◽  
Traditional Use

Wireless sensor networks (WSN) have tremendous potential in many environmental and structural health monitoring applications including, gas, temperature, pressure and humidity monitoring, motion detection, and hazardous materials detection. Recent advances in CMOS-technology, IC manufacturing, and networking utilizing Bluetooth communications have brought down the total power requirements of wireless sensor nodes to as low as a few hundred microwatts. Such nodes can be used in future dense ad-hoc networks by transmitting data 1 to 10 meters away. For communication outside 10 meter ranges, data must be transmitted in a multi-hop fashion. There are significant implications to replacing large transmission distance WSN with multiple low-power, low-cost WSN. In addition, some of the relay nodes could be mounted on mobile robotic vehicles instead of being stationary, thus increasing the fault tolerance, coverage and bandwidth capacity of the network. The foremost challenge in the implementation of a dense sensor network is managing power consumption for a large number of nodes. The traditional use of batteries to power sensor nodes is simply not scalable to dense networks, and is currently the most significant barrier for many applications. Self-powering of sensor nodes can be achieved by developing a smart architecture which utilizes all the environmental resources available for generating electrical power. These resources can be structural vibrations, wind, magnetic fields, light, sound, temperature gradients and water currents. The generated electric energy is stored in the matching media selected by the microprocessor depending upon the power magnitude and output impedance. The stored electrical energy is supplied on demand to the sensors and communications devices. This paper shows the progress in our laboratory on powering stationary and mobile untethered sensors using a fusion of energy harvesting approaches. It illustrates the prototype hardware and software required for their implementation including MEMS pressure and strain sensors mounted on mobile robots or stationary, power harvesting modules, interface circuits, algorithms for interrogating the sensor, wireless data transfer and recording.

Sign in / Sign up

Export Citation Format

Share Document