Lübben, R. (2022). Forecasting TCP s Rate to Speed up Slow Start. IEEE Open Journal of the Computer Society, 1–9. http://doi.org/10.1109/OJCS.2022.3208701
Lübben, R., & Misfeld, N. (2022). Exploring the Measurement Lab Open Dataset for Internet Performance Evaluation: The German Internet Landscape. Electronics, 11. http://doi.org/10.3390/electronics11010162
Abstract
The Measurement Lab (MLab) provides a large and open collection of Internet performance measurements. We make use of it to look at the state of the German Internet by a structured analysis, in which we carve out expressive results from the dataset to identify busy hours and days, the impact of server locations and congestion control protocols, and compare Internet service providers. Moreover, we examine the impact of the COVID-19 lockdown in Germany. We observe that only parts of the Internet show a performance degradation at the beginning of the lockdown and that a large impact in performance depends on the network the servers are located in. Furthermore, the evolution of congestion control algorithms is reflected by performance improvements. For our analysis, we focus on the busy hours. From the end-user perspective, this time is of most interest to identify if the network can support challenging services such as video streaming or cloud gaming at these intervals.
Lübben, R. (2022). Forecasting TCP s Rate to Speed up Slow Start. IEEE Open Journal of the Computer Society, 1–9. http://doi.org/10.1109/OJCS.2022.3208701
Irshad, M., Börstler, J., & Petersen, K. (2022). Supporting refactoring of BDD specifications—An empirical study. Information and Software Technology, 141, 106717.
Petersen, K., Carlson, J., Papatheocharous, E., & Wnuk, K. (2021). Context checklist for industrial software engineering research and practice. Computer Standards \& Interfaces, 78, 103541.
Irshad, M., Britto, R., & Petersen, K. (2021). Adapting Behavior Driven Development (BDD) for large-scale software systems. Journal of Systems and Software, 177, 110944.
Petersen, K., & eri, J. S. M. (2021). Preliminary Evaluation of a Survey Checklist in the Context of Evidence-based Software Engineering Education. In ENASE (S. 437–444).