A Graph Transformation-Based Approach for the Validation of Checkpointing Algorithms in Distributed Systems

International audience—Autonomic Computing Systems are oriented to pre-vente the human intervention and to enable distributed systems to manage themselves. One of their challenges is the efficient monitoring at runtime oriented to collect information from which the system can automatically repair itself in case of failure. Quasi-Synchronous Checkpointing is a well-known technique, which allows processes to recover in spite of failures. Based on this technique, several checkpointing algorithms have been developed. According to the checkpoint properties detected and ensured, they are classified into: Strictly Z-Path Free (SZPF), Z-Path Free (ZPF) and Z-Cycle Free (ZCF). In the literature, the simulation has been the method adopted for the performance evaluation of checkpointing algorithms. However, few works have been designed to validate their correctness. In this paper, we propose a validation approach based on graph transformation oriented to automatically detect the previous mentioned checkpointing properties. To achieve this, we take the vector clocks resulting from the algorithm execution, and we model it into a causal graph. Then, we design and use transformation rules oriented to verify if in such a causal graph, the algorithm is exempt from non desirable patterns, such as Z-paths or Z-cycles, according to the case

A Mechanism for the Causal Ordered Set Representation in Large-Scale Distributed Systems

International audienceDistributed systems have undergone a very fast evolution these last years. Large-scale distributed systems have become an integral part of everyday life with the development of new large-scale applications, consisting of thousands of computers and supporting millions of users. Examples include global Internet services, cloud computing systems, " big data " analytics platforms, peer-to-peer systems, wireless sensor networks and so on. The recent research addresses questions related to the way one may design, build, operate and maintain large-scale distributed systems. An other question related to such area, is how to represent causal dependencies in such systems in a minimal way. In general, causal dependencies can be established according to the Happened-Before Relation (HBR), which was introduced by Lamport. The HBR is a strict partial order, and therefore, one main problem linked to it is the combinatorial state explosion. The Immediate Dependency Relation (IDR) and the Causal Order Set Abstraction (CAOS) present a solution for such a problem. In this paper, we propose a mechanism which uses the concepts HBR, IDR, CAOS to model a large-scale distributed system execution in the form of the minimal graph (IDR graph) and the compact graph (CAOS graph). This mechanism is implemented in C++. The results of its execution are given here. The resultant causal graphs can be used for different purposes, such as for the design of more efficient algorithms, validation, verification, and/or the debugging of the existing ones, among others

An Efficient Validation Approach for Quasi-Synchronous Checkpointing oriented to Distributed Diagnosability

International audienceThe 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