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Abstract-Autonomic Computing Systems are oriented to prevente 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. QuasiSynchronous 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.

SUMMARYCommunication-induced checkpointing (CIC) has two main advantages: first, it allows processes in a distributed computation to take asynchronous checkpoints, and secondly, it avoids the domino effect. To achieve these, CIC algorithms piggyback information on the application messages and take forced local checkpoints when they recognize potentially dangerous patterns. The main disadvantages of CIC algorithms are the amount of overhead per message and the induced storage overhead. In this paper we present a communication-induced checkpointing algorithm called Scalable Fully-Informed (S-FI) that attacks the problem of message overhead. For this, our algorithm modifies the Fully-Informed algorithm by integrating it with the immediate dependency principle. The S-FI algorithm was simulated and the result shows that the algorithm is scalable since the message overhead presents an under-linear growth as the number of processes and/or the message density increase.