scholarly journals An Attenuation Model of Node Signals in Wireless Underground Sensor Networks

2021 ◽  
Vol 13 (22) ◽  
pp. 4642
Author(s):  
Meng Han ◽  
Zenglin Zhang ◽  
Jie Yang ◽  
Jiayun Zheng ◽  
Wenting Han
Keyword(s):  
Sensor Networks ◽  
Signal Transmission ◽  
Sensor Nodes ◽  
Burial Depth ◽  
Horizontal Distance ◽  
Signal Attenuation ◽  
Experimental Conditions ◽  
Soil Medium ◽  
Attenuation Model ◽  
Wireless Underground Sensor Networks

Wireless underground sensor networks (WUSN) consist of sensor nodes that are operated in the soil medium. To evaluate the signal attenuation law of WUSN nodes, in this study, a WUSN node signal transmission test platform was built in the laboratory. The signal intensity data of WUSN nodes under different experimental conditions were obtained by orthogonal test. The WUSN node signal attenuation model was established. The test results show that the transmission of WUSN node signals in the soil medium is seriously affected by soil moisture content, node burial depth, soil compactness, and horizontal distance between nodes. The R2 of the models was between 0.790 and 0.893, and the RMSE of the models was between 2.489 and 4.192 dbm. Then, the WUSN node signal attenuation model involving the four factors was established. The R2 and RMSE of the model were, respectively, 0.822 and 4.87 dbm. The WUSN node signal attenuation model established in this paper can facilitate WUSN node deployment.

scholarly journals Energy-Spectral Efficiency Optimization in Wireless Underground Sensor Networks Using Salp Swarm Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mariem Ayedi ◽  
Esraa Eldesouky ◽  
Jabeen Nazeer
Keyword(s):  
Sensor Networks ◽  
Spectral Efficiency ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Green Communication ◽  
Soil Medium ◽  
Salp Swarm Algorithm ◽  
Battery Capacity ◽  
Swarm Algorithm ◽  
Wireless Underground Sensor Networks

Achieving high data rate transmission is critically constrained by green communication metrics in Wireless Sensor Networks (WSNs). A unified metric ensuring a successful compromise between the energy efficiency (EE) and the spectral efficiency (SE) is, then, an interesting design criterion in such systems. In this paper, we focus on EE-SE tradeoff optimization in Wireless Underground Sensor Networks (WUSNs) where signals penetrate through a challenging lossy soil medium and nodes’ power supply is critical. Underground sensor nodes gather and send sensory information to underground relay nodes which amplify-and-retransmit received signals to an aboveground sink node. We propose to optimize source and relay powers used for each packet transmission using an efficient recent metaheuristic optimization algorithm called Salp Swarm Algorithm (SSA). Thus, the optimal source and relay transmission powers, which maximize the EE-SE tradeoff under the maximum allowed transmission powers and the initial battery capacity constraints, are obtained. Further, we study the case where the underground medium properties are dynamic and change from a transmission to another. For this situation, we propose to allocate different maximum node powers according to the soil medium conditions. Simulation results prove that our proposed optimization achieves a significant EE-SE tradeoff and prolongs the network’s lifetime compared to the fixed allocation node power scheme. Additional gain is obtained in case of dynamic medium conditions.

Research on Signal Transmission Property of Wireless Sensor Networks for Test System

2012 ◽  
Vol 166-169 ◽  
pp. 1091-1096
Author(s):  
Jianpeng Sun ◽  
Chao Fu Zhu ◽  
Jin Long Zhao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Transmission Rate ◽  
Stress Test ◽  
Signal Transmission ◽  
Test System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Node ◽  
Visual Conditions

By using the key technology of wireless sensor networks, a stress test system was designed, which takes the M2110 wireless sensor networks as a platform. Based on the hardware design and software design of TinyOS2.0 sensor nodes and gateway nodes, the signal transmission performance of wireless sensor networks for the stress test system was tested and researched. In the visual conditions, the maximum communication distance of M2110 wireless node is up to 601 meters. In the non-visual conditions, M2110 wireless node also has a certain signal transmission capacity. On the situation of multi-hop nodes network, the success rate of data transfer has relation to the transmission rate of data packet and the number of hops for nodes.

scholarly journals Wireless Underground Sensor Networks: Channel Modeling and Operation Analysis in the Terahertz Band

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Mustafa Alper Akkaş ◽  
Radosveta Sokullu
Keyword(s):  
Sensor Networks ◽  
Crude Oil ◽  
Oil Recovery ◽  
Channel Model ◽  
Ground Surface ◽  
Path Loss ◽  
Channel Modeling ◽  
Sensor Nodes ◽  
Main Challenge ◽  
Wireless Underground Sensor Networks

Wireless underground sensor networks (WUSNs) are networks of sensor nodes operating below the ground surface, which are envisioned to provide real-time monitoring capabilities in the complex underground environments consisting of soil, water, oil, and other components. In this paper, we investigate the possibilities and limitations of using WUSNs for increasing the efficiency of oil recovery processes. To realize this, millimeter scale sensor nodes with antennas at the same scale should be deployed in the confined oil reservoir fractures. This necessitates the sensor nodes to be operating in the terahertz (THz) range and the main challenge is establishing reliable underground communication despite the hostile environment which does not allow the direct use of most existing wireless solutions. The major problems are extremely high path loss, small communication range, and high dynamics of the electromagnetic (EM) waves when penetrating through soil, sand, and water and through the very specific crude oil medium. The objective of the paper is to address these issues in order to propose a novel communication channel model considering the propagation properties of terahertz EM waves in the complex underground environment of the oil reservoirs and to investigate the feasible transmission distances between nodes for different water-crude-oil-soil-CO2compositions.

Hybrid Wireless Underground Sensor Networks: Quantification of Signal Attenuation in Soil

2009 ◽  
Vol 8 (3) ◽  
pp. 755-761 ◽  
Author(s):  
H. R. Bogena ◽  
J. A. Huisman ◽  
H. Meier ◽  
U. Rosenbaum ◽  
A. Weuthen
Keyword(s):  
Sensor Networks ◽  
Signal Attenuation ◽  
Wireless Underground Sensor Networks

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

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