Multi-Cloud Data Analytics as a Service (MCloudDaaS)

Multi-Cloud Data Analytics as a Service (MCloudDaaS) combines the benefits of Big Data Analytics and Multi-Cloud Systems.
Many companies struggle to find a convenient and affordable data analytic solution. Most cloud providers does not provide an easy to use cloud system Furthermore, clients have concerns like the lack of security, which leads to a mistrust against cloud services.
In order to overcome such barriers, MCloudDaaS provides innovative functionalities with regards to security, scalability and fault-tolerance. In addition, MCloudDaaS avoids a vendor lock-in of the customers, who would be in a traditional cloud system economically dependent of the provided DaaS solutions and therefore increasing costs when moving to a different cloud provider. To increase the trust of the customer, high security standards will be integrated. Moreover, MCloudDaaS provides rich management functionalities, predictions of performance and management for scalability. As a result, this leads to CAPEX reduction, because customers can switch to a cheaper provider.

The overall goal of the project is the development of a flexible, secure and on-demand hybrid cloud platform for big data analytics. The project has the following main objectives:

1. Enabling interoperability and portability, in order to overcome the vender lock-in to give the customer the freedom to choose between different providers.
2. Increased trust and security. Einbettung von hohen Sicherheitsmaßnahmen. For this reason, MCloudDaaS provides enhanced techniques for advanced access/usage control, key management, encryption techniques and secure data sharing.
3. Enhanced management capabilities for easy usage. The installation, configuration and customization of big data solutions will be realized through automated mechanisms and increases the usability of the overall system.
4. High scalability and availability. An automatic management for scalability and fault tolerance drives to better performance of analytics jobs.

Our research group Complex and Distributed IT-Systems (CIT) is going to work on the realization of a Big Data Analytics Multi-Cloud Service Management in this project.

• This includes the integration of Multi-Cloud Big Data Services, like the management and installation of Apache Hadoop and Apache Flink on different cloud-infrastructures.
• The development of autonomous scaling management, which increases the performance for analytic jobs by automatically scaling worker nodes.
• Integration of data encryption techniques and data access control management.