Today, there is an increasing number of peering agreements between Hypergiants and networks that benefit millions of end-user. However, the majority of Autonomous Systems do not currently enjoy the benefit of interconnecting directly with Hypergiants to optimally select the path for delivering Hypergiant traffic to their users. In this paper, we develop and evaluate an architecture that can help this long tail of networks. With our proposed architecture, a network establishes an out-of-band communication channel with Hypergiants that can be two or more AS hops away and, optionally, with the transit provider. This channel enables the exchange of network information to better assign requests of end-users to appropriate Hypergiant servers. Our analysis using operational data shows that our architecture can optimize, on average, 15% of Hypergiants’ traffic and 11% of the overall traffic of networks that do not interconnect with Hypergiants. The gains are even higher during peak hours when available capacity can be scarce, up to 46% for some Hypergiants.

In this paper, we report on a measurement study by researchers from several institutions that collected and analyzed network data to assess the impact of the first wave of COVID-19 (February-June 2020) on the Internet traffic. The datasets from Internet Service Providers, Internet Exchange Points, and academic networks, primarily in Europe, provide a unique view on the changes of Internet traffic due to pandemic and the lockdown that forced hundreds of millions of citizens to stay and work from home. The analysis shows that the increase of Internet traffic was about 15-20 % within a couple of weeks, an increase that is typically spread over multiple months under typical operation. However, traffic during peak hours does not increase by more than 5 %. The increase was noticeably higher for specific applications, e.g., remote work applications, teleconferencing, video on demand; in some cases up to 200 %. However, overall, the Internet reacted well to these unprecedented times.

In March 2020, the World Health Organization declared the Corona Virus 2019 (COVID-19) outbreak a global pandemic. As a result, billions of people were either encouraged or forced by their governments to stay home to reduce the spread of the virus. This caused many to turn to the Internet for work, education, social interaction, and entertainment. With the Internet demand rising at an unprecedented rate, the question of whether the Internet could sustain this additional load emerged. To answer this question, this paper will review the impact of the first year of the COVID-19 pandemic on Internet traffic in order to analyze its performance. In order to keep our study broad, we collect and analyze Internet traffic data from multiple locations at the core and edge of the Internet. From this, we characterize how traffic and application demands change, to describe the "new normal,"and explain how the Internet reacted during these unprecedented times.