Abstract
Since cloud applications are usually large-scale, it is too expensive to enhance the reliability of all components for building highly reliable cloud applications. Therefore, we need to identify significant components which have great impact on the system reliability. FTCloud, an existing approach, ranks the components only considering the impact of component internal failures and ignoring error propagation. However, error propagation is also an important factor on the system reliability. To attack the problem, we propose an improved component ranking framework, named DCR, to identify significant components in cloud applications. DCR employs two individual algorithms to rank the components twice and determines a set of the most significant components based on the two ranking results. In addition, DCR does not require information of component invocation frequencies. Extensive experiments are provided to evaluate DCR and compare it with FTCloud. The experimental results show that DCR outperforms FTCloud in almost all cases.
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