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new conference paper: Anycast Polarization in The Wild

Our new paper “Anycast Polarization in The Wild” will appear at the 2024 Conference on Passive and Active Measurements (PAM 2024).

From the abstract:

The left figure shows the impacts of polarization. The Dallas, USA site for a CDN is receiving traffic from all over the world due to polarization. The red dots indicate high latency from Europe and Asia, even if Europe and India have anycast sites in their continent. We show this type of polarization is not uncommon. The right figure shows how a change in the routing configuration can improve the polarization problem. We can see almost no red dots from Europe and Asia continents.

IP anycast is a commonly used method to associate users with services provided across multiple sites, and if properly used, it can provide efficient access with low latency. However, prior work has shown that polarization can occur in global anycast services, where some users of that service are routed to an anycast site on another continent, adding 100 ms or more latency compared to a nearby site. This paper describes the causes of polarization in real-world anycast and shows how to observe polarization in third-party anycast services. We use these methods to look for polarization and its causes in 7986 known anycast prefixes. We find that polarization occurs in more than a quarter of anycast prefixes, and identify incomplete connectivity to Tier-1 transit providers and route leakage by regional ISPs as common problems. Finally, working with a commercial CDN, we show how small routing changes can often address polarization, improving latency for 40% of clients, by up to 54%.

This paper is a joint work by ASM Rizvi from USC/ISI and Akamai Technologies, Tingshan Huang from Akamai Technologies, Rasit Esrefoglu from Akamai Technologies, and John Heidemann from USC/ISI. ASM Rizvi and John Heidemann’s work was partially supported by DARPA under Contract No. HR001120C0157. John Heidemann’s work was also partially supported by the NFS projects CNS-2319409, CRI-8115780, and CNS-1925737. ASM Rizvi’s work was begun while on an internship at Akamai.

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new paper “Improving Coverage of Internet Outage Detection in Sparse Blocks”

We will publish a new paper “Improving Coverage of Internet Outage Detection in Sparse Blocks” by Guillermo Baltra and John Heidemann in the Passive and Active Measurement Conference (PAM 2020) in Eugene, Oregon, USA, on March 30, 2020.

From the abstract:

There is a growing interest in carefully observing the reliability of the Internet’s edge. Outage information can inform our understanding of Internet reliability and planning, and it can help guide operations. Active outage detection methods provide results for more than 3M blocks, and passive methods more than 2M, but both are challenged by sparse blocks where few addresses respond or send traffic. We propose a new Full Block Scanning (FBS) algorithm to improve coverage for active scanning by providing reliable results for sparse blocks by gathering more information before making a decision. FBS identifies sparse blocks and takes additional time before making decisions about their outages, thereby addressing previous concerns about false outages while preserving strict limits on probe rates. We show that FBS can improve coverage by correcting 1.2M blocks that would otherwise be too sparse to correctly report, and potentially adding 1.7M additional blocks. FBS can be applied retroactively to existing datasets to improve prior coverage and accuracy.

This paper defines two algorithms: Full Block Scanning (FBS), to address false outages seen in active measurements of sparse blocks, and Lone Address Block Recovery (LABR), to handle blocks with one or two responsive addresses. We show that these algorithms increase coverage, from a nominal 67% (and as low as 53% after filtering) of responsive blocks before to 5.7M blocks, 96% of responsive blocks.