Scenwise has developed the ScenarioDesigner to support road authorities in creating response plans. The response plans describe which actions the operator should take in order to manage different traffic situations such as accidents, large scale events This thesis elaborates on the process as well as the end-product created during the Bachelor End Project The BEP is a 10 week compulsory project to complete the Computer Science and Engineering program of the Delft University of Technology. It was conducted between 11 November 2019 and 11 February 2020. During the first two weeks the group focused on researching the problem, the possible solutions and traffic management in general. The subsequent 8 weeks were designated to the development of the product. The product was developed for ScenWise, a company that focuses on innovation within traffic management. In addition to evaluating the product, this thesis gives recommendations for a following group working on extending the product. Finally, the group would like to thank the client ScenWise, specifically K.F. Chan for providing the project as well as teaching us about the domain knowledge of the client. Furthermore, the group wants to thank Dr. A. Katsifodimos for the coaching throughout the project as well as Ir. O.W. Visser for giving the opportunity to do the BEP in the second quarter of the academic year.

Containerization has become a fundamental component of software development and the continuous integration and continuous delivery (CI/CD) pipeline. However, the energy overhead of containerization solutions such as Docker results not only in higher costs but also has environmental consequences. Currently, the energy efficiency of containers is often neglected, since developers mainly focus on small image size and time efficiency. Furthermore, there is also a lack of understanding about the impact of base images on the container during runtime. Therefore, the objective of this thesis is to assess the impact of base image selection on the energy efficiency of containerized workloads. This is done by running an empirical study, in which we conduct experiments with a diverse set of real-world workloads and base images. The results of this study show that the base image can have a significant impact on the energy efficiency of the container. However, the magnitude of this impact in practice depends on the workload. For some workloads (i.e. databases) this impact is more significant in practice than for others (i.e. gaming servers). While there is no single best or worst image across all workloads, Alpine is often the least energy-efficient option. Furthermore, the execution time of the container is only correlated to the energy consumption for CPU-intensive workloads. Therefore, besides image size and time efficiency, it is important to consider energy efficiency in the selection criteria as well when considering sustainable practices in software engineering.