A Wireless Sensor Networks' Analytics System for Predicting Performance in On-Demand Deployments

Otero, Carlos E.; Haber, Rana; Peter, Adrian M.; Alsayyari, Abdulaziz; Kostanic, Ivica

doi:10.1109/jsyst.2014.2320324

Cited by 29 publications

(17 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The work in [3] presents empirical RF data and path loss models for two outdoor environments of WSN (i.e., long grass and sparse tree.). While the long grass environment is characterized by a flat terrain with long weeds, the sparse tree environment has a ground similar to the long grass terrain with random presence of trees.…”

Section: Results Analysis and Comparisonmentioning

confidence: 99%

“…For practical applications, prediction of the WSN deployment performance depends on one's ability to model the propagation of the radio signal between the nodes, which depends fundamentally on the type of terrain and the type of objects and foliage on the terrain [3]. Therefore, there is a critical need for creating terrain-specific models that are appropriate for predicting signal propagation in WSN.…”

Section: Introductionmentioning

confidence: 99%

“…In [3], for example, the authors present two empirical path loss models based on RF measurements of WSNs deployed in sparse tree and long grass environments. The parameters of the two models were found to be different, with a PLE of 2.55 for the long grass and 3.34 for the sparse tree.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An empirical path loss model for Wireless Sensor Network deployment in a concrete surface environment

Alsayyari

Kostanic

Otero

2015

2015 IEEE 16th Annual Wireless and Microwave Technology Conference (WAMICON)

Self Cite

View full text Add to dashboard Cite

This paper presents a path loss model for predicting signal propagation of wireless sensor nodes deployed in concrete surface environments. To create the model, radio frequency (RF) measurements were collected through Wireless Sensor Network (WSN) deployment in such environment. From the actual measurements, the parameters of the log-normal shadowing model are fine-tuned to develop an accurate path loss model. In addition, the presented RF measurements and empirical path loss model are compared with measurements and models obtained from long-grass and sparse-tree environments, which were presented in a previous work. The results from the comparison of such different environments show significant differences in path loss and empirical models' parameters. Furthermore, the comparison between the proposed model and largely used path loss models such as free space path loss (FSPL) and Two-Ray demonstrate the inaccuracy of these models in predicting path loss between wireless sensor nodes deployed in concrete surface environments.

show abstract

Section: Results Analysis and Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An empirical path loss model for Wireless Sensor Network deployment in a concrete surface environment

Alsayyari

Kostanic

Otero

2015

2015 IEEE 16th Annual Wireless and Microwave Technology Conference (WAMICON)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, the minimal value of K v is used to establish formula (18). When the binary perception model is adopted and the boundary effect is not taken into consideration, the relationship of the expected value of the coverage quality with the number of the working nodes,…”

Section: Redundancy Coveragementioning

confidence: 99%

Optimization coverage conserving protocol with authentication in wireless sensor networks

Sun

Long-xing

et al. 2017

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

In the k-coverage process of target nodes, substantial data redundancy occurs, which leads to the phenomenon of congestion, reducing the network communication capability and coverage as well as accelerating network energy consumption. Therefore, this article proposes an Optimization Coverage Conserving Protocol with Authentication. This protocol provides a solution to obtain the largest coverage probability for multi-nodes. In the optimization and authenticated calculation, the protocol provides the calculation method and verification process of the expected value of multinode coverage; when the moving target nodes are continuously covered, this protocol provides a process to solve for the focused target nodes; when there is redundancy coverage, this article provides a process to calculate the coverage probability when any sensor node is covered by a redundant node. Furthermore, through comparisons of the coverage quality and network lifetime with other algorithms, the performance indexes of this protocol have been substantially increased by the simulation experiment, which verified the effectiveness and viability of the protocol in this article.

show abstract

“…From the radio propagation point of view, the RSS is the most used and easy to measure parameter to quantify the link quality [53]. In Table IV, the mean value and the standard deviation of the RSS for all links in the network are reported.…”

Section: Radio Link Statisticsmentioning

confidence: 99%

A Robust Wireless Sensor Network for Landslide Risk Analysis: System Design, Deployment, and Field Testing

et al. 2016

View full text Add to dashboard Cite

In this paper we propose a wireless sensor network (WSN) designed for monitoring and risk management of landslides, where data collected by sensors are delivered through the network to a remote unit (RU) for on-line analysis and alerting. To ensure fast deployment, robustness in harsh environments, and very long lifetime, the sensor nodes and the communication protocol have been specifically conceived so that the network is self-organizing, fault tolerant, and adaptive. The WSN has been installed on a landslide located in Torgiovannetto (Italy) for an experimental campaign of several months where performance metrics, such as radio link and path statistics as well as battery levels, have been collected. These metrics demonstrated the effectiveness of the network protocols to manage self-organization, node failures, low link quality and unexpected battery depletion. With negligible human intervention during the pilot experiment, the WSN revealed a very high level of robustness, which makes it suitable to monitor landslides in critical scenarios.

show abstract

A Wireless Sensor Networks' Analytics System for Predicting Performance in On-Demand Deployments

Cited by 29 publications

References 22 publications

An empirical path loss model for Wireless Sensor Network deployment in a concrete surface environment

An empirical path loss model for Wireless Sensor Network deployment in a concrete surface environment

Optimization coverage conserving protocol with authentication in wireless sensor networks

A Robust Wireless Sensor Network for Landslide Risk Analysis: System Design, Deployment, and Field Testing

Contact Info

Product

Resources

About