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Cloud Kotta: Enabling Secure and Scalable Data Analytics in the Cloud

Babuji, Yadu; Chard, Kyle; Gerow, Aaron and Duede, Eamon. 2016. 'Cloud Kotta: Enabling Secure and Scalable Data Analytics in the Cloud'. In: IEEE International Conference on Big Data (BigData 2016). Washington DC, United States 5-8 December 2016. [Conference or Workshop Item]

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Abstract or Description

Distributed communities of researchers rely increasingly on valuable, proprietary, or sensitive datasets. Given the growth of such data, especially in fields new to data-driven research like the social sciences and humanities, coupled with what are often strict and complex data-use agreements, many research communities now require methods that allow secure, scalable and cost-effective storage and analysis. Here we present CLOUD KOTTA: a cloud-based data management and analytics framework. CLOUD KOTTA delivers an end-to-end solution for coordinating secure access to large datasets, and an execution model that provides both automated infrastructure scaling and support for executing analytics near to the data. CLOUD KOTTA implements a fine-grained security model ensuring that only authorized users may access, analyze, and download protected data. It also implements automated methods for acquiring and configuring low-cost storage and compute resources as they are needed. We present the architecture and implementation of CLOUD KOTTA and demonstrate the advantages it provides in terms of increased performance and flexibility. We show that CLOUD KOTTA’s elastic provisioning model can reduce costs by up to 16x when compared with statically provisioned models.

Item Type:

Conference or Workshop Item (Paper)

Identification Number (DOI):

https://doi.org/10.1109/BigData.2016.7840616

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
2016Published

Event Location:

Washington DC, United States

Date range:

5-8 December 2016

Item ID:

22719

Date Deposited:

09 Jan 2018 14:55

Last Modified:

15 Jul 2018 04:42

URI:

http://research.gold.ac.uk/id/eprint/22719

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