Localization in Wireless Sensor Networks Using Link-Quality Values: A Real Test-Bed Implementation

2021 ◽  
pp. 321-330
Author(s):  
Tuhin Majumder ◽  
Punyasha Chatterjee
Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3621 ◽  
Author(s):  
Peio Lopez-Iturri ◽  
Mikel Celaya-Echarri ◽  
Leyre Azpilicueta ◽  
Erik Aguirre ◽  
José Astrain ◽  
...  

In this work, the combination of capabilities provided by Wireless Sensor Networks (WSN) with parameter observation in a school garden is employed in order to provide an environment for school garden integration as a complementary educational activity in primary schools. Wireless transceivers with energy harvesting capabilities are employed in order to provide autonomous system operation, combined with an ad-hoc implemented application called MySchoolGardenApp, based on a modular software architecture. The system enables direct parameter observation, data analysis and processing capabilities, which can be employed by students in a cloud based platform. Providing remote data access allows the adaptation of content to specific classroom/homework needs. The proposed monitoring WSN has been deployed in an orchard located in the schoolyard of a primary school, which has been built with EnOcean’s energy harvesting modules, providing an optimized node device as well network layout. For the assessment of the wireless link quality and the deployment of the modules, especially the central module which needs to receive directly the signals of all the sensor modules, simulation results obtained by an in-house developed 3D Ray Launching deterministic method have been used, providing coverage/capacity estimations applicable to the specific school environment case. Preliminary trials with MySchoolGardenApp have been performed, showing the feasibility of the proposed platform as an educational resource in schools, with application in specific natural science course content, development of technological skills and the extension of monitoring capabilities to new context-aware applications.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5164
Author(s):  
Changsun Shin ◽  
Meonghun Lee

The swarm intelligence (SI)-based bio-inspired algorithm demonstrates features of heterogeneous individual agents, such as stability, scalability, and adaptability, in distributed and autonomous environments. The said algorithm will be applied to the communication network environment to overcome the limitations of wireless sensor networks (WSNs). Herein, the swarm-intelligence-centric routing algorithm (SICROA) is presented for use in WSNs that aim to leverage the advantages of the ant colony optimization (ACO) algorithm. The proposed routing protocol addresses the problems of the ad hoc on-demand distance vector (AODV) and improves routing performance via collision avoidance, link-quality prediction, and maintenance methods. The proposed method was found to improve network performance by replacing the periodic “Hello” message with an interrupt that facilitates the prediction and detection of link disconnections. Consequently, the overall network performance can be further improved by prescribing appropriate procedures for processing each control message. Therefore, it is inferred that the proposed SI-based approach provides an optimal solution to problems encountered in a complex environment, while operating in a distributed manner and adhering to simple rules of behavior.


2018 ◽  
Vol 62 (6) ◽  
pp. 820-837 ◽  
Author(s):  
Faisal Ahmed ◽  
Corentin Kervadec ◽  
Yannick Le Moullec ◽  
Gert Tamberg ◽  
Paul Annus

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6430
Author(s):  
Ngoc Huy Nguyen ◽  
Myung Kyun Kim

Although mature industrial wireless sensor network applications increasingly require low-power operations, deterministic communications, and end-to-end reliability, it is very difficult to achieve these goals because of link burstiness and interference. In this paper, we propose a novel link quality estimation mechanism named the burstiness distribution metric, which uses the distribution of burstiness in the links to deal with variations in wireless link quality. First, we estimated the quality of the link at the receiver node by counting the number of consecutive packets lost in each link. Based on that, we created a burstiness distribution list and estimated the number of transmissions. Our simulation in the Cooja simulator from Contiki-NG showed that our proposal can be used in scheduling as an input metric to calculate the number of transmissions in order to achieve a reliability target in industrial wireless sensor networks.


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