Temporal and spatial outlier detection in wireless sensor networks
| Autor: | Nguyen Huu Thai, Hoc Thai Nguyen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Computer science temporal outlier Real-time computing lcsh:Electronics InformationSystems_DATABASEMANAGEMENT lcsh:TK7800-8360 outlier detection Electronic Optical and Magnetic Materials lcsh:Telecommunication spatial outlier symbols.namesake ComputingMethodologies_PATTERNRECOGNITION lcsh:TK5101-6720 symbols Anomaly detection Electrical and Electronic Engineering Gaussian process Wireless sensor network Hampel Identifier |
| Zdroj: | ETRI Journal, Vol 41, Iss 4, Pp 437-451 (2019) |
| ISSN: | 1225-6463 |
| Popis: | Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed. Unfortunately, most of these techniques still have some potential limitations, that is, (a) high rate of false positives, (b) high time complexity, and (c) failure to detect outliers online. Moreover, these approaches mainly focus on either temporal outliers or spatial outliers. Therefore, this paper aims to introduce novel algorithms that successfully detect both temporal outliers and spatial outliers. Our contributions are twofold: (i) modifying the Hampel Identifier (HI) algorithm to achieve high accuracy identification rate in temporal outlier detection, (ii) combining the Gaussian process (GP) model and graph‐based outlier detection technique to improve the performance of the algorithm in spatial outlier detection. The results demonstrate that our techniques outperform the state‐of‐the‐art methods in terms of accuracy and work well with various data types. |
| Databáze: | OpenAIRE |
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