An efficient validation approach for quasi-synchronous checkpointing oriented to distributed diagnosability

Abstract

The Autonomic Computing paradigm is oriented towards enabling complex distributed systems to manage themselves, even in faulty situations. The diagnosability analysis is a priori study through which a system can be self-aware about its current state. It is from the determination of a consistent state that a system can take some actions to repair or reconfigure itself. Nevertheless, in a distributed system it is hard to determine consistent states since we cannot observe simultaneously all the local variables of different processes. In this context, the challenge is to efficiently monitor the system execution over time to capture trace information in order to determine if the system accomplishes both functional and non-functional requirements. Quasi-Synchronous Checkpointing is a technique that collects information from which a system can establish consistent snapshots. Based on this technique, several checkpointing algorithms have been developed. According to the checkpoint properties, they are classified into: Strictly Z-Path Free (SZPF), Z-Path Free (ZPF) and Z-Cycle Free (ZCF). Checkpointing algorithms are often evaluated with regard to performance, generally through simulation. However, their correctness has been mildly studied. In this paper, we propose an efficient validation approach based on a graph transformation oriented towards the automatic detection of the aforementioned properties.

Adaptive and reconfigurable software systems and architectures

“…The work of Khlif et al (2016) presents a graph transformationbased approach for validation of quasi-synchronous checkpointing algorithms. They model algorithm execution as a happened-before graph or immediate dependency graph.…”