scholarly journals An Effective Sensor Deployment Scheme that Ensures Multilevel Coverage of Wireless Sensor Networks with Uncertain Properties

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1831 ◽  
Author(s):  
Yu-Ning Chen ◽  
Wu-Hsiung Lin ◽  
Chiuyuan Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Probability ◽  
Sensor Node ◽  
Fundamental Problem ◽  
Wireless Sensor ◽  
Sensor Deployment ◽  
Sensing Model ◽  
Definition Of ◽  
Probabilistic Sensing Model

The coverage problem is a fundamental problem for almost all applications in wireless sensor networks (WSNs). Many applications even impose the requirement of multilevel (k) coverage of the region of interest (ROI). In this paper, we consider WSNs with uncertain properties. More precisely, we consider WSNs under the probabilistic sensing model, in which the detection probability of a sensor node decays as the distance between the target and the sensor node increases. The difficulty we encountered is that there is no unified definition of k-coverage under the probabilistic sensing model. We overcome this difficulty by proposing a “reasonable” definition of k-coverage under such a model. We propose a sensor deployment scheme that uses less number of deployed sensor nodes while ensuring good coverage qualities so that (i) the resultant WSN is connected and (ii) the detection probability satisfies a predefined threshold p th , where 0 < p th < 1 . Our scheme uses a novel “zone 1 and zone 1–2” strategy, where zone 1 and zone 2 are a sensor node’s sensing regions that have the highest and the second highest detection probability, respectively, and zone 1–2 is the union of zones 1 and 2. The experimental results demonstrate the effectiveness of our scheme.

Energy-Efficient Coverage Based on Probabilistic Sensing Model in Wireless Sensor Networks

2010 ◽  
Vol 14 (9) ◽  
pp. 833-835 ◽  
Author(s):  
Jiming Chen ◽  
Junkun Li ◽  
Shibo He ◽  
Youxian Sun ◽  
Hsiao-Hwa Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Sensing Model ◽  
Probabilistic Sensing Model

scholarly journals Discrete Path Selection and Entropy Based Sensor Node Failure Detection in Wireless Sensor Networks

2016 ◽  
Vol 16 (3) ◽  
pp. 137-153 ◽  
Author(s):  
K. Spoorthi ◽  
Saha Snehanshu ◽  
Mathur Archana
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Low Cost ◽  
Failure Detection ◽  
Path Selection ◽  
Wireless Sensor ◽  
Sensing Model ◽  
Cost Efficient ◽  
Almost All

Abstract Exertion of wireless sensor networks has been increasing in recent years, and it imprints in almost all the technologies such as machine industry, medical, military and civil applications. Due to rapid growth in electronic fabrication technology, low cost, efficient, multifunctional and accurate sensors can be produced and thus engineers tend to incorporate many sensors in the area of deployment. As the number of sensors in the field increases, the probability of failure committed by these sensors also increases. Hence, efficient algorithms to detect and recover the failure of sensors are paramount. The current work concentrates mainly on mechanisms to detect sensor node failures on the basis of the delay incurred in propagation and also the energy associated with sensors in the field of deployment. The simulation shows that the algorithm plays in the best possible way to detect the failure in sensors. Finally, the Boolean sensing model is considered to calculate the network coverage of the wireless sensor network for various numbers of nodes in the network.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

scholarly journals TSCH and RPL Joining Time Model for Industrial Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3904
Author(s):  
Jose Vera-Pérez ◽  
Javier Silvestre-Blanes ◽  
Víctor Sempere-Payá
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Industry 4.0 ◽  
Wireless Sensor ◽  
Lossy Networks ◽  
Industrial Wireless Sensor Networks ◽  
Time Model ◽  
Industrial Internet ◽  
Channel Hopping ◽  
Definition Of

Wireless sensor networks (WSNs) play a key role in the ecosystem of the Industrial Internet of Things (IIoT) and the definition of today’s Industry 4.0. These WSNs have the ability to sensor large amounts of data, thanks to their easy scalability. WSNs allow the deployment of a large number of self-configuring nodes and the ability to automatically reorganize in case of any change in the topology. This huge sensorization capacity, together with its interoperability with IP-based networks, allows the systems of Industry 4.0 to be equipped with a powerful tool with which to digitalize a huge amount of variables in the different industrial processes. The IEEE 802.15.4e standard, together with the access mechanism to the Time Slotted Channel Hopping medium (TSCH) and the dynamic Routing Protocol for Low-Power and Lossy Networks (RPL), allow deployment of networks with the high levels of robustness and reliability necessary in industrial scenarios. However, these configurations have some disadvantages in the deployment and synchronization phases of the networks, since the time it takes to synchronize the nodes is penalized compared to other solutions in which access to the medium is done randomly and without channel hopping. This article proposes an analytical model to characterize the behavior of this type of network, based on TSCH and RPL during the phases of deployment along with synchronization and connection to the RPL network. Through this model, validated by simulation and real tests, it is possible to parameterize different configurations of a WSN network based on TSCH and RPL.

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