Problem Detection in Real-Time Systems by Trace Analysis. (6th January 2016)
- Record Type:
- Journal Article
- Title:
- Problem Detection in Real-Time Systems by Trace Analysis. (6th January 2016)
- Main Title:
- Problem Detection in Real-Time Systems by Trace Analysis
- Authors:
- Côté, Mathieu
Dagenais, Michel R. - Other Names:
- Sukharev Valeriy Academic Editor.
- Abstract:
- Abstract : This paper focuses on the analysis of execution traces for real-time systems. Kernel tracing can provide useful information, without having to instrument the applications studied. However, the generated traces are often very large. The challenge is to retrieve only relevant data in order to find quickly complex or erratic real-time problems. We propose a new approach to help finding those problems. First, we provide a way to define the execution model of real-time tasks with the optional suggestions of a pattern discovery algorithm. Then, we show the resulting real-time jobs in a Comparison View, to highlight those that are problematic. Once some jobs that present irregularities are selected, different analyses are executed on the corresponding trace segments instead of the whole trace. This allows saving huge amount of time and execute more complex analyses. Our main contribution is to combine the critical path analysis with the scheduling information to detect scheduling problems. The efficiency of the proposed method is demonstrated with two test cases, where problems that were difficult to identify were found in a few minutes.
- Is Part Of:
- Advances in computer engineering. Volume 2016(2016)
- Journal:
- Advances in computer engineering
- Issue:
- Volume 2016(2016)
- Issue Display:
- Volume 2016, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 2016
- Issue:
- 2016
- Issue Sort Value:
- 2016-2016-2016-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-01-06
- Subjects:
- Computer engineering -- Periodicals
Computer engineering
Periodicals
621.39 - Journal URLs:
- https://www.hindawi.com/journals/aceng/ ↗
- DOI:
- 10.1155/2016/9467181 ↗
- Languages:
- English
- ISSNs:
- 2356-6620
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10337.xml