Concurrent Checkpointing for Embedded Real-Time Systems

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/ThesisMasters Thesis Computer Engineering 201

Lightweight Memory Checkpointing

Memory check pointing is a pivotal technique in systems reliability, with applications ranging from crash recovery to replay debugging. Unfortunately, many traditional memory check pointing use-cases require high-frequency checkpoints, something for which existing application-level solutions are not well-suited. The problem is that they incur either substantial run-time performance overhead, or poor memory usage guarantees. As a result, their application in practice is hampered. This paper presents Lightweight Memory Check pointing (LMC), a new user-level memory check pointing technique that combines low performance overhead with strong memory usage guarantees for high check pointing frequencies. To this end, LMC relies on compiler-based instrumentation to shadow the entire memory address space of the running program and incrementally checkpoint modified memory bytes in a LMC-maintained shadow state. Our evaluation on popular server applications demonstrates the viability of our approach in practice, confirming that LMC imposes low performance overhead with strictly bounded memory usage at runtime