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Exploiting Big Data in Engineering Adaptive Cloud Services

Our research into adaptive cloud services has shown that adaptation can require the storage and analysis of potentially large amounts of data [martin13book, mian13pe]. The position I argue in my talk is that big data has an important role to play in the engineering of adaptive software systems, in general, and adaptive cloud services, in particular. I use our own research to support my claim. In our research into QoS-aware management for cloud services big data analytics are required in a number of the component services, specifically cloud provider recommendation, workload forecasting, performance prediction and monitoring. In each of these component services big data is used to generate models to facilitate the necessary decision-making. We see that the big challenge in all these cases is the need to adapt the models when the workload and/or environment changes. We also observe that, with the creation and management of these models, model management will be an important addition to the adaptive middleware.

References

[martin13book]P. Martin, S. Soltani, W. Powley and M. Hassannezhad, ``QoS-Aware Cloud Application Management'', in Advances in Parallel Computing: Clouds, Big Data and Data-Intensive Computing, February 2013.
[mian13pe]R. Mian, P. Martin, F. Zulkernine and J. Vazquez-Poletti, ``Towards Building Performance Models for Data-intensive Workloads in Public Clouds'', in Proc of 4th International Conference on Performance Engineering, Prague, Czech Republic, April 2013, pp. 259--270.