The team of AI Investments actively participates in research projects in time series prediction, machine learning and novel Cloud Computing. Below is the list of publications coauthored by members of our team.
Publication date: 2019/3/27
Conference: Workshops of the International Conference on Advanced Information Networking and Applications
Publisher: Springer, Cham
Description: Cost savings is one of the main motivations for deploying commercial applications in the Cloud. These savings are more pronounced for applications with varying computational needs, like Computational Intelligence (CI) applications. However, continuously deploying, adapting, and decommissioning the provided Cloud resources manually is challenging, and autonomous deployment support is necessary. This paper discusses the specific challenges of CI applications and provide calculations to show that dynamic use of Cloud resources will result in significant cost benefits for CI applications.
Publication date: 2019
Conference: 22nd International Conference on Business Information Systems
Publisher: Springer, Cham
Description: Serverless computing is currently taking a momentum due to the main benefits it introduces which include zero administration and reduced operation cost for applications. However, not all application components can be made serverless in sight also of certain limitations with respect to the deployment of such components in corresponding serverless platforms. In this respect, there is currently a great need for managing hybrid applications, i.e., applications comprising both normal and serverless components. Such a need is covered in this paper through extending the Melodic platform in order to support the deployment and adaptive provisioning of hybrid, cross-cloud applications. Apart from analysing the architecture of the extended platform, we also explain what are the relevant challenges for supporting the management of serverless components and how we intend to confront them. One use case is also utilised in order to showcase the main benefits of the proposed platform.