scholarly journals A Novel Routing Algorithm with Bernoulli Sampling-based Link Quality Estimation in Wireless Sensor Networks

2021 ◽  
Author(s):  
Chao Meng
Keyword(s):  
Data Transmission ◽  
High Performance ◽  
Routing Algorithm ◽  
Wireless Transmission ◽  
Link Quality ◽  
Accurate Estimation ◽  
Quality Estimation ◽  
Calculation Results ◽  
Novel Method ◽  
Link Quality Estimation

Abstract Link quality is important and can greatly affect the performance of wireless transmission algorithms and protocols. Currently, researchers have proposed a variety of approaches to implement link quality estimation. However, the estimated result of link quality is not accurate enough and the error is large, so they may lead to the failure of routing algorithm and protocol. In this paper, a novel method is proposed to achieve the more accurate estimation of link quality than before. This method employs Bernoulli sampling-based algorithm to complete the estimation of link quality. The problem is modeled as calculation of estimators based on Bernoulli sampling data. The authors further prove that the calculation results are accurate by probability theory. Furthermore, according to link quality estimation, the authors also provide a centralized routing algorithm and a distributed improvement algorithm in order to switch the data transmission on the better quality link. Finally, the extensive experiment results indicate that the proposed methods obtain high performance in terms of energy consumption and accuracy.

scholarly journals A Hybrid Reliable Routing Algorithm Based on LQI and PRR in Industrial Wireless Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jie Li ◽  
Yang Pan ◽  
Shijian Ni ◽  
Feng Wang
Keyword(s):  
Wireless Networks ◽  
Routing Algorithm ◽  
Link Quality ◽  
Quality Estimation ◽  
Received Signal Strength Indicator ◽  
Industrial Environment ◽  
Reliable Routing ◽  
Industrial Wireless Networks ◽  
Link Quality Indicator ◽  
Link Quality Estimation

In Industrial Wireless Networks (IWNs), the communication through Machine-to-Machine (M2M) is often affected by the noise in the industrial environment, which leads to the decline of communication reliability. In this paper, we investigate how to improve route stability through M2M in an industrial environment. We first compare different link quality estimations, such as Signal-Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Packet Reception Ratio (PRR), and Expected Transmission Count (ETX). We then propose a link quality estimation combining LQI and PRR. Finally, we propose a Hybrid Link Quality Estimation-Based Reliable Routing (HLQEBRR) algorithm for IWNs, with the object of maximizing link stability. In addition, HLQEBRR provides a recovery mechanism to detect node failure, which improves the speed and accuracy of node recovery. OMNeT++-based simulation results demonstrate that our HLQEBRR algorithm significantly outperforms the Collection Tree Protocol (CTP) algorithm in terms of end-to-end transmission delay and packet loss ratio, and the HLQEBRR algorithm achieves higher reliability at a small additional cost.

scholarly journals Machine Learning for Wireless Link Quality Estimation: A Survey

2021 ◽  
pp. 1-1
Author(s):  
Gregor Cerar ◽  
Halil Yetgin ◽  
Mihael Mohorcic ◽  
Carolina Fortuna
Keyword(s):  
Machine Learning ◽  
Link Quality ◽  
Wireless Link ◽  
Quality Estimation ◽  
Link Quality Estimation

scholarly journals Radio Link Quality Estimation in Low-Power Wireless Networks

2013 ◽  
Author(s):  
Nouha Baccour ◽  
Anis Koubâa ◽  
Claro Noda ◽  
Hossein Fotouhi ◽  
Mário Alves ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Low Power ◽  
Link Quality ◽  
Radio Link ◽  
Quality Estimation ◽  
Low Power Wireless Networks ◽  
Link Quality Estimation

Link Quality Estimation in Industrial Temporal Fading Channel With Augmented Kalman Filter

2019 ◽  
Vol 15 (4) ◽  
pp. 1936-1946 ◽  
Author(s):  
Fei Qin ◽  
Qilong Zhang ◽  
Wuxiong Zhang ◽  
Yang Yang ◽  
Jinliang Ding ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Fading Channel ◽  
Link Quality ◽  
Quality Estimation ◽  
Link Quality Estimation

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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