Mining Cloud Environments Usage Data

Karim M. Sobh, Ahmed Rafea, and Amr El-Kadi


data mining, cloud computing, event collection, PMML


In cloud environments, resources are being shared between different organizations, and service providers of cloud resources require an efficient mechanism for metering resource usage to be able to charge customers fairly, based on actual resource utilization rather than resource rental time. One of the main challenges is the incompatibility of different usage data formats generated from different software and cloud resources, which need to be correlated and processed seamlessly to achieve a streamline metering process. In this paper, an architecture is proposed for collecting usage data and presenting it in a portable inter-operable format. Usage data is presented in Predictive Model Markup Language PMML, where data models exchange is adopted rather than the traditional data unification approaches. An extensible interpreted Cloud Metering Markup Language, CMML, is proposed for distributed usage data collection and processing. Finally, a prototype for CPU usage correlation is presented to demonstrate the applicability of the framework.

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