Correlating Time Series Signals and Event Logs in Embedded Systems
In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/21/7128 |
| _version_ | 1797511787804884992 |
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| author | Kazimierz Krosman Janusz Sosnowski |
| author_facet | Kazimierz Krosman Janusz Sosnowski |
| author_sort | Kazimierz Krosman |
| collection | DOAJ |
| description | In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems. |
| first_indexed | 2024-03-10T05:52:59Z |
| format | Article |
| id | doaj.art-7f3016852ffb45d2a1a87499a238802e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:52:59Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-7f3016852ffb45d2a1a87499a238802e2023-11-22T21:37:01ZengMDPI AGSensors1424-82202021-10-012121712810.3390/s21217128Correlating Time Series Signals and Event Logs in Embedded SystemsKazimierz Krosman0Janusz Sosnowski1Institute of Computer Science, Warsaw University of Technology, 00-665 Warsaw, PolandInstitute of Computer Science, Warsaw University of Technology, 00-665 Warsaw, PolandIn many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.https://www.mdpi.com/1424-8220/21/21/7128signal processingembedded systemsdata synchronisation issuesdevice monitoringtime series analysis |
| spellingShingle | Kazimierz Krosman Janusz Sosnowski Correlating Time Series Signals and Event Logs in Embedded Systems Sensors signal processing embedded systems data synchronisation issues device monitoring time series analysis |
| title | Correlating Time Series Signals and Event Logs in Embedded Systems |
| title_full | Correlating Time Series Signals and Event Logs in Embedded Systems |
| title_fullStr | Correlating Time Series Signals and Event Logs in Embedded Systems |
| title_full_unstemmed | Correlating Time Series Signals and Event Logs in Embedded Systems |
| title_short | Correlating Time Series Signals and Event Logs in Embedded Systems |
| title_sort | correlating time series signals and event logs in embedded systems |
| topic | signal processing embedded systems data synchronisation issues device monitoring time series analysis |
| url | https://www.mdpi.com/1424-8220/21/21/7128 |
| work_keys_str_mv | AT kazimierzkrosman correlatingtimeseriessignalsandeventlogsinembeddedsystems AT januszsosnowski correlatingtimeseriessignalsandeventlogsinembeddedsystems |