A data sample algorithm applied to wireless sensor network with disruptive connections
| Autor: | Israel L. C. Vasconcelos, Carlos M. S. Figueiredo, Andre L. L. Aquino, Ivan C. Martins |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
Computer science 0202 electrical engineering electronic engineering information engineering Drop (telecommunication) 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology Random walk Algorithm Wireless sensor network Gaussian random field |
| Zdroj: | Computer Networks. 146:1-11 |
| ISSN: | 1389-1286 |
| DOI: | 10.1016/j.comnet.2018.09.006 |
| Popis: | This paper presents a data sample algorithm applied to wireless sensor network applications with disruptive connections. Additionally, it defines a model for delay-tolerant sensor network where drop strategies are applied to improve the phenomenon coverage in an application that monitors the forest temperature incidence for wildlife observation. The environmental application model comprises: i) Phenomenon generation based on a Gaussian random field along with the Matern covariance model; ii) Sensing nodes deployment based on simple sequential inhibition process with a mobile sink node following a random walk process; iii) Data collection and processing based on a data-aware drop strategy; and iv) Phenomenon reconstruction based on simple kriging interpolation. This research employed the data-aware drop strategy and compared it with the others, reported in the literature. Besides the satisfactory application of this model, the results show that the performance of data-aware drop strategy is twice better than conventional ones in all evaluated scenarios. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect