The DNS maps human-readable identifiers to computer-friendly identifiers and relies on a reverse tree architecture to achieve this mapping. Backed by economic incentives, the DNS has become increasingly complex with data being shared among multiple au- tonomous stakeholders. The diversity of autonomous stakeholders limits data collection, access and sharing to researchers. For in- stance, each of stakeholder controls limited parts of the DNS space, thereby limiting analysis of real-world DNS behaviour. We aim to design and develop a software framework to unify diverse and large-scale public DNS data sources. The platform will facilitate the access to public DNS data by providing an efficient way of processing and analyzing large amounts of distributed data regard- less of the DNS data format. Thus, the framework will help enable reproducibility in DNS studies.

In this study, we evaluate the performance of different Dynamic Adaptive Streaming over HTTP (DASH) video rate adaptation algorithms over mobile networks. More specifically, we compare and evaluate the performance of Basic, Segment Aware Rate Adaptation (SARA), and Buffer-Based Rate Adaptation (BBA) rate adaptation algorithms over the 4G-Long Term Evolution (LTE) networks of three Mobile Network Operators (MNOs): Telenor, Telia, and ICE. We use the Measuring Mobile Broadband Networks in Europe (MONROE) testbed for conducting measurements, and OpenVQ toolbox for evaluation.