abstract: The Internet of Things ecosystem has spawned a wide variety of embedded real-time systems that complicate the identification and resolution of bugs in software. The methods of concurrent checkpoint provide a means to monitor the application state with the ability to replay the execution on like hardware and software, without holding off and delaying the execution of application threads. In this thesis, it is accomplished by monitoring physical memory of the application using a soft-dirty page tracker and measuring the various types of overhead when employing concurrent checkpointing. The solution presented is an advancement of the Checkpoint and Replay In Userspace (CRIU) thereby eliminating the large stalls and parasitic operation for each successive checkpoint. Impact and performance is measured using the Parsec 3.0 Benchmark suite and 4.11.12-rt16+ Linux kernel on a MinnowBoard Turbot Quad-Core board. / Dissertation/Thesis / Masters Thesis Computer Engineering 2018
| Identifer | oai:union.ndltd.org:asu.edu/item:51723 |
| Date | January 2018 |
| Contributors | Prinke, Michael L (Author), Lee, Yann-Hang (Advisor), Shrivastava, Aviral (Committee member), Zhao, Ming (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 62 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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