scholarly journals Impact of Energy and Link Quality Indicator with Link Quality Estimators in Wireless Sensor Networks

2014 ◽  
Vol 6 (4) ◽  
pp. 23-32 ◽  
Author(s):  
Bouyahi Mohamed ◽  
Zrelli Amira ◽  
Rezig Houria ◽  
Ezzedine Tahar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Quality Indicator ◽  
Link Quality ◽  
Wireless Sensor ◽  
Link Quality Indicator

scholarly journals Environmental Impacts on Hardware-Based Link Quality Estimators in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5327
Author(s):  
Wei Liu ◽  
Yu Xia ◽  
Daqing Zheng ◽  
Jian Xie ◽  
Rong Luo ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Environmental Changes ◽  
Signal To Noise Ratio ◽  
Link Quality ◽  
Wireless Sensor ◽  
Transitional Region ◽  
Environment Changes ◽  
Fluctuation Range ◽  
Link Quality Indicator

Hardware-based link quality estimators (LQEs) in wireless sensor networks generally use physical layer parameters to estimate packet reception ratio, which has advantages of high agility and low overhead. However, many existing studies didn’t consider the impacts of environmental changes on the applicability of these estimators. This paper compares the performance of typical hardware-based LQEs in different environments. Meanwhile, aiming at the problematic Signal-to-Noise Ratio (SNR) calculation used in existing studies, a more reasonable calculation method is proposed. The results show that it is not accurate to estimate the packet reception rate using the communication distance, and it may be useless when the environment changes. Meanwhile, the fluctuation range of the Received Signal Strength Indicator (RSSI) and SNR will be affected and that of Link Quality Indicator (LQI) is almost unchanged. The performance of RSSI based LQEs may degrade when the environment changes. Fortunately, this degradation is mainly caused by the change of background noise, which could be compensated conveniently. The best environmental adaptability is gained by LQI and SNR based LQEs, as they are almost unaffected when the environment changes. Moreover, LQI based LQEs are more accurate than SNR based ones in the transitional region. Nevertheless, compared with SNR, the fluctuation range of LQI is much larger, which needs a larger smoothing window to converge. In addition, the calculation of LQI is typically vendor-specific. Therefore, the tradeoff between accuracy, agility, and convenience should be considered in practice.

A Link Evaluation Method Employing Statistical Means of Received Signal Strength Indicator and Link Quality Indicator for Wireless Sensor Networks

2013 ◽  
Vol 470 ◽  
pp. 722-728
Author(s):  
Xuan Jie Ning ◽  
Hai Zhao ◽  
Mao Fan Yang ◽  
Hua Feng Chai
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Evaluation Method ◽  
Ieee 802.15.4 ◽  
Signal Strength ◽  
Link Quality ◽  
Wireless Sensor ◽  
Wireless Link ◽  
Received Signal Strength Indicator ◽  
Link Quality Indicator

This paper is concerned with a wireless receiving link evaluation method using statistical means of received signal strength indicator (RSSI) and link quality indicator (LQI) based on the IEEE 802.15.4 protocol for wireless sensor networks. Traditional methods using single RSSI and single LQI based on the IEEE 802.11 protocol have the disadvantage of the inaccurate evaluation. In this paper, we carry out a quantitative emulation experiment via computing statistical means of RSSI and LQI based on wireless sensor networks protocol of IEEE 802.15.4. Tested numerical values are analyzed using MATLAB and SPSS by defining the wireless link evaluation sensitivity. Result curves of RSSI to packet reception rate (PRR) and LQI to PRR we finally derive are shown that statistical means of RSSI and LQI can obtain the status information of receiving links more accurately, compared with the traditional wireless link evaluation using single RSSI and single LQI.

scholarly journals Integration of Autonomous Wireless Sensor Networks in Academic School Gardens

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3621 ◽  
Author(s):  
Peio Lopez-Iturri ◽  
Mikel Celaya-Echarri ◽  
Leyre Azpilicueta ◽  
Erik Aguirre ◽  
José Astrain ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Primary Schools ◽  
Data Access ◽  
Link Quality ◽  
Educational Activity ◽  
Wireless Sensor ◽  
Observation Data ◽  
School Garden

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.

scholarly journals Swarm-Intelligence-Centric Routing Algorithm for Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5164
Author(s):  
Changsun Shin ◽  
Meonghun Lee
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Performance ◽  
Ad Hoc ◽  
Routing Algorithm ◽  
Optimal Solution ◽  
Link Quality ◽  
Wireless Sensor ◽  
Control Message

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.

Autonomous Wireless Sensor Networks: Implementation of Transient Computing and Energy Prediction for Improved Node Performance and Link Quality

2018 ◽  
Vol 62 (6) ◽  
pp. 820-837 ◽  
Author(s):  
Faisal Ahmed ◽  
Corentin Kervadec ◽  
Yannick Le Moullec ◽  
Gert Tamberg ◽  
Paul Annus
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Link Quality ◽  
Wireless Sensor ◽  
Energy Prediction

scholarly journals Link Quality Estimation from Burstiness Distribution Metric in Industrial Wireless Sensor Networks

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6430
Author(s):  
Ngoc Huy Nguyen ◽  
Myung Kyun Kim
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Link Quality ◽  
Wireless Sensor ◽  
Industrial Wireless Sensor Networks ◽  
Quality Estimation ◽  
Network Applications ◽  
Power Operations ◽  
Link Quality Estimation

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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