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Privacy preserving minimal observability for composite transactional services

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Abstract

For complex services composed of many (component) services, logging is an integral middleware aspect, especially for providing transactions and monitoring. In the event of a failure, the log allows us to deduce the cause of failure (diagnosis) and recover by compensating the executed services (atomicity). However, for heterogeneous services with parts of the functionality provided by multiple organizations, logging details of all executed services is often impracticable due to privacy/security constraints. Also, logging is expensive in terms of both time and space. Thus, we are interested in determining the minimal number of services that need to be logged, and which is still sufficient to know with certainty the actual sequence of executed services from any given log. Further to privacy issues, the complexity of determining a minimal set of such services to log is actually NP-Complete. To solve both issues, we resort to considering each component service as a grey box. Logs are recorded and kept local to each component, and a black-box view of the implementation details of each component is provided. In particular, a service which is reused as a component several times (often observed in real-life services) need not be re-computed each time. We show that this dramatically decreases the complexity up to 2 exponentials. For large monolithic component services that cannot be decomposed simply, we also provide heuristics to compute a small (but not necessarily minimal) number of services to log, and experimentally analyze their accuracy and performance.

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Notes

  1. Universal Description Discovery & Integration (UDDI). http://uddi.xml.org/

  2. OWL-S: Semantic Markup for Web Services. http://uddi.xml.org/

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Acknowledgments

This work is supported by Create ACTIVEDOC and ANR DOCFLOW projects. Most of this work has been done while the first author was at IRISA/INRIA Rennes.

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Authors and Affiliations

  1. Iprova, Lausanne, Switzerland

    Debmalya Biswas & Blaise Genest

Authors
  1. Debmalya Biswas
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  2. Blaise Genest
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Corresponding author

Correspondence to Blaise Genest.

Additional information

Parts of this work appeared in the extended abstracts (Biswas and Genest 2008; Biswas et al. 2008).

Appendix

Appendix

Computing the Largest Component

In this section, we address the problem that the hierarchical structure specifying the components at each level is not available. It can be the case if the service was build in a monolithic fashion, or more pragmatically if it is not accessible anymore. That is, given a (flat representation of a) composite service, we would like to recover the hierarchical structure from it. Also, the effectiveness of our divide and conquer algorithms (Section 4.2) are clearly proportional to the size the components, that is, the larger the components the better as large components can possibly be refined further (which would imply that we should be interested in the smallest component C, however then the M C would be large). Towards this end, we show how to recover the largest component from a given composite service M in Appendix A. First, we present a linear time (in the number of transitions) algorithm to compute a smallest component C of an FSM M, knowing its initial, final state and an outgoing transition of the initial state.

Table 1
Full size table

The above algorithm can be iteratively invoked to compute the set S C of all components of an FSM M. We now give an algorithm to compute a largest component of M.

Table 2
Full size table

Using the above algorithm, a largest component of given service M can computed in quadratic time. The algorithm can thus be called inductively until there are no more components in the determined component FSM N of a level, and then the hierarchical structure of M has been obtained.

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Biswas, D., Genest, B. Privacy preserving minimal observability for composite transactional services. Discrete Event Dyn Syst 24, 611–646 (2014). https://doi.org/10.1007/s10626-013-0177-z

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