Results from NDT only measure paths from users to their transit ISPs (dark grey line). For example, M-Lab nodes mostly connect to transit ISPs (e.g., Level3 and TATA). Measuring from cloud providers, such as Amazon EC2, Google Compute Engine (GCE), and Microsoft Azure, can better reveal the performance impact of congestion on cloud-ISP links than existing throughput measurements from the edge, due to the location of available vantage points (Figure 1). However, these is no scientific study to focus on measuring the performance, reliability and resiliency of these cloud-ISP links. This pandemic induced shift in network traffic and amplified the concerns regarding network congestion between these critical infrastructures, as the degraded performance and quality of experience (QoE) of cloud-based applications could negatively impact work and learning performance. Microsoft recently reported a 775% increase in Teams' online meeting users in a one month period in Italy due to social distancing, and the application of higher bandwidth constraints to cloud applications to mitigate network congestion. These interconnections have limited capacity, and are prone to congestion. While sophisticated traffic engineering (e.g., SWAN, B4 ) enables cloud providers to dynamically reroute traffic to mitigate congestion, interconnections between ISPs and cloud providers (cloud-ISP links) rely on peering links at IXPs, private peering links, or transit providers. 1 Introduction and MotivationIn the crisis of the coronavirus pandemic, the Internet is facing unprecedented surges of traffic induced by the use of cloud-based tele-communicating and remote education tools for real-time video meetings and online classes.
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