No abstract

The COVID-19 pandemic dramatically changed the way of living of billions of people in a very short time frame. In this paper, we evaluate the impact on the Internet latency caused by the increased amount of human activities that are carried out on-line. The study focuses on Italy, which experienced significant restrictions imposed by local authorities, but results about Spain, France, Germany, Sweden, and the whole of Europe are also included. The analysis of a large set of measurements shows that the impact on the network can be significant, especially in terms of increased variability of latency. In Italy we observed that the standard deviation of the average additional delay – the additional time with respect to the minimum delay of the paths in the region – during lockdown is times as much as the value before the pandemic. Similarly, in Italy, packet loss is times as much as before the pandemic. The impact is not negligible also for the other countries and for the whole of Europe, but with different levels and distinct patterns.

Portolan is a crowdsourcing-based system aimed at building an annotated graph of the Internet: the smartphones of participating volunteers are used as mobile monitors to collect measures about the network that surrounds them, then results are conveyed on a central server where they are aggregated. Thus, differently from all the other Internet monitoring systems, which are based on fixed infrastructure, Portolan rely on a multitude of mobile sensing nodes. While this paves the way to the opportunity of having detailed and geo-referenced measures, the design of the systems has to take into account additional difficulties such as scalability, coordination and smartphones' reachability. Besides describing the Portolan's architecture, this paper also shows some preliminary results that confirm the validity of the proposed approach

The location of Internet hosts is frequently used in distributed applications and networking services. Examples include customized advertising, distribution of content, and position-based security. Unfortunately the relationship between an IP address and its position is in general very weak. This motivates the study of measurement-based IP geolocation techniques, where the position of the target host is actively estimated using the delays between a number of landmarks and the target itself. This paper discusses an IP geolocation method based on crowdsourcing where the smartphones of users operate as landmarks. Since smartphones rely on wireless connections, a specific delay-distance model was derived to capture the characteristics of this novel operating scenario