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1. Map-Reduce computation model With M-R, the user only needs to provide a map function and a reduce function while the system interaction and parallel execution are handled by the platform. Such ease of adapting contributes to the taking-off of M-R. 1 In-Database Map-Reduce A parallel database engine, such as HP Neoview, is built on a cluster of interconnected server nodes; each node can hold multiple query processing servers which are either query executors (ESP) or data processor (DP2). A DP2 is responsible for retrieving data from the database, as well as for certain local query processing.

3 Conclusion The goal of the investigation was met! We proved that the methodology has potential to support the execution of risk management in the activities Establishing the Context and Risk Assessment. The application of the methodology in a real context, submitting it to the treatment of the technological risk, namely to the unavailability event, not only let us to prove its potential in this case, but also let us note its generality. If the methodology will be provided with data relative to other events, or to other types of organizational risks, it will operate normally.

1 Evaluation QoS Distribution Generation Result for Web Services In Figure 1, solid lines represent the QoS distributions generated by QoSDIST. It can be seen that QoS distributions obtained by QoSDIST are able to represent R. Meersman et al. ): OTM 2010 Workshops, LNCS 6428, pp. 10–11, 2010. 5 0 2 Response Time 0 2000 4000 6000 4 x 10 (a) Random Image PDF 8000 10000 Response Time 12000 14000 16000 (b) Dilbert PDF Fig. 1. QoS Probability Distributions for Web Services the real QoS distributions for Web services while standard statistical distributions (t location-scale and normal distributions) do not have this ability.

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