Diploma and Master Theses (authored and supervised):

L. Gao:
"On Provisioning and Configuring Ensembles of IoT, Network Functions and Cloud Resources";
Supervisor: H. Truong; Institute of Information Systems Engineering, Distributed Systems Group, 2018; final examination: 2018-10-01.

English abstract:
With the rapid growth of the Internet of Things (IoT) and their integration with cloud computing systems, there is a need for effective management of resources that make up an IoT-based system. These IoT Cloud Systems are made up of resources which may be physical or virtual such as sensors, network functions, software artifacts or cloud services. There are a number of IoT Cloud Systems currently studied in literature with various applications from vehicle fleet management to datacenter maintenance. IoT Cloud System scenarios require rapid provisioning and configuration of resources at runtime to adapt to changing user requirements.
With the growing popularity of *aaS (X as a Service) many organizations and third parties who have become IoT and Cloud resource providers. Each resource provider uses different methods and APIs to manage their resources. However, this is at the expense of today´s users who need to provision and use entire end-to-end ensembles of
resources. The overhead that is generated in order to interface separately with different resource providers is significant. We aim to reduce this overhead and the knowledgebase required for a user to rapidly provision and configure ensembles of IoT, network functions
and cloud services to form functional systems. To this end, we propose a framework that aims to provision and configure end-to-end resource ensembles in a dynamic and on-demand environment. Our framework harmonizes the resource and resource provider representation through the abstraction of higher level information models. With the
abstractions these information models provide, we are able provide a unified API to manage resources without dealing with the associated low-level information for different types of resource and infrastructures. Finally, we provide an evaluation of our framework
on functionality and performance.

Created from the Publication Database of the Vienna University of Technology.