Danila Valko

Eike Schulte, Jan Sören Schwarz, Malte Stomberg et al.

In a mosaic, a tessera is a single stone. We introduce tesserae for the co-simulation framework mosaik, where they are sets of entities. They allow for a visual, intuitive, and yet systematic description of simulation scenarios by allowing their entities to be created together and the entities of two tesserae to be connected simultaneously, while ensuring that multidirectional data-flow between tesserae remains consistent without further manual synchronization. We further present an extension of mosaik by a graphical user interface (GUI) based on these tesserae, enabling the drag-and-drop creation of co-simulation setups and their execution. The GUI aims to make mosaik more accessible to users previously excluded by its script-based nature. At the same time, it preserves mosaik's flexibility, extensibility, and modular architecture.

Danila Valko, Daniel Kudenko

Recent estimates put the carbon footprint of Bitcoin and Ethereum at an average of 64 and 26 million tonnes of CO2 per year, respectively. To address this growing problem, several possible approaches have been proposed in the literature: creating alternative blockchain consensus mechanisms, applying redundancy reduction techniques, utilizing renewable energy sources, and employing energy-efficient devices, etc. In this paper, we follow the second avenue and propose an efficient approach based on reinforcement learning that improves the block broadcasting scheme in blockchain networks. The analysis and experimental results confirmed that the proposed improvement of the block propagation scheme could cleverly handle network dynamics and achieve better results than the default approach. Additionally, our technical integration of the simulator and developed RL environment can be used as a complete solution for further study of new schemes and protocols that use RL or other ML techniques.