v2(GraphQL)

The new AS Rank API^v2 is ready for use. This new version reflects a move from a RESTful (v1) API to a GraphQL (v2) API. This will allow clients to create queries that specify which values they require and contain multiple resources. GraphQL, as a strongly-typed language, allows clients to know what data is available, in what format, and verify responses.

The User Interface (UI) can be found at http://asrank.caida.org. The Application Programming Interface (API^v2) serves at https://api.asrank.caida.org/v2/graphql and GraphiQL interface can be found at https://api.asrank.caida.org/docs.

We will be operating AS Rank API^v1 (http://as-rank.caida.org/api/v1) until March 1st, 2020, but it will no longer be updated. Current users should migrate to the v2 API before this date. Contact asrank-info@caida.org for migration assistance.

For those unfamiliar with GraphQL, it is a bit of a paradigm shift from the use of a RESTful API, in that GraphQL requires the client to specify precisely which values it needs. In the following example, the client wants to know an ASN’s transit degree. With a normal RESTful API, the client must retrieve the full record and extract the information it wants. A GraphQL API client must specify that it wants the ASN’s transit degree.

# request ASN 3356's degree
query={
   asn(asn:"3356") {
      asnDegree {
         transit
      }
   }
}
        

data={
   "asn": {
      "asnDegree": {
         "transit": 5255
    }
}

# request ASN 3356's record
/asns/3356?populate=1
                

GraphQL supports mixed record queries. The same query can include different record types, and can specify bindings (“joins”) between those resources. This approach reduces the number of API queries needed to retrieve related resources.

# request ASN 3356's asnName and 
# organization LPL-141-ARIN's rank.

query={
   asn(asn:"3356") {
      asnName
      organization {
        orgId
      }
   }
   organization(orgId:"LPL-141-ARIN") {
      rank
   }
}
        

# request ASN 3356's asnName and 
# it's organization's rank.

query={
   asn(asn:"3356") {
      asnName
      organization {
         rank
      }
   }
}
        

data={
    "asn": {
      "asnName": "LEVEL3"
      "organization": {
         "orgId": "LPL-141-ARIN" 
      }
    },
    "organization": {
      "rank": 1,
    }
}
        

data={
    "asn": {
      "asnName": "LEVEL3",
      "organization": {
        "rank": 1
      }
    }
  }
}
        

# request ASN 3356's record
/asns/3356?populate=1
                 

data={
  "name": "LEVEL3",
  "org": {
    "id": "LPL-141-ARIN",
    "name": "Level 3 Parent, LLC"
  },
  "clique": "true",
  "source": "ARIN",
  "cone": {
     ...                

data={
    "name": "Level 3 Parent, LLC",
    "rank": "1",
    "degree": {
      "asn": {
        "transit": 6999,
        "global": 7024
      },
      "org": {
        ....
                    

CAIDA intern Alex Gamero-Garrido, a PhD student in Computer Science and Engineering at UC San Diego, was selected as one of eleven recipients of the 2019 Microsoft Research Dissertation Grants. Each dissertation grant provides funding to doctoral students at North American universities who are underrepresented in the field of computing. This is the third year Microsoft Research has offered these research grants. Microsoft Research scientists with expertise in the students’ topic areas reviewed the more than 200 proposals submitted and identified students pursuing technically excellent and societally impactful research.

Alex Gamero-Garrido’s dissertation, “Inferring Country-Level Transit Influence of Autonomous Systems” may be of interest to networking and cybersecurity researchers, policy makers and operators:

Our work explores the country-level influence exerted by transit providers, a set of networking organizations that often have less direct contact with users, but who are nonetheless responsible for delivering an important fraction of transnational traffic into and out of many countries, and who may have the capability to observe, manipulate, or disrupt some of that traffic. For instance, an accidental misconfiguration or a state-ordered disconnection implemented by one of these operators may render popular services delivered on the Internet (such as email or social media) unreachable in entire regions. These concerns are not abstract, as previous instances of state-ordered disconnections have propagated to other countries and temporarily disabled some of the world’s most popular services there. By studying the ways in which these operators (Autonomous Systems) connect to one another and to the rest of the Internet, we aim to highlight each country’s relative risk exposure.

Congratulations, Alex G!

Originally announced on the Microsoft Research Blog.

In late April 2019, social media was reportedly blocked and access to the Internet was shutdown in Benin during its 2019 parliamentary elections.

In this report, the Open Observatory of Network Interference (OONI) and the Center for Applied Internet Data Analysis (CAIDA) teams share OONI, IODA, and RIPE Atlas network measurement data that corroborate and provide insight into these recent censorship events in Benin.
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The CAIDA annual report summarizes CAIDA’s activities for 2018, in the areas of research, infrastructure, data collection and analysis. Our research projects span Internet topology, routing, security, economics, future Internet architectures, and policy. Our infrastructure, software development, and data sharing activities support measurement-based internet research, both at CAIDA and around the world, with focus on the health and integrity of the global Internet ecosystem. The executive summary is excerpted below:
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(Forgot to post this earlier, this is old news by now but fwiw..)
I presented at the 10th FTC Hearing on Competition and Consumer Protection in the 21st century this March, held in Washington D.C., giving a talk about Technological Developments in Broadband Networking which aims to address this question: Which (recent and expected) technological developments, or lack thereof, are important for understanding the competitiveness of the industry or impacts on the public interest?

A webcast of the presentation (my talk begins at 10m30s) is available. I also participated in a discussion panel, also webcast.

On December 12-13, 2018, CAIDA and the Massachusetts Institute of Technology (MIT) hosted the (invitation-only) 9th interdisciplinary Workshop on Internet Economics (WIE) at the University of California San Diego in La Jolla, CA.

The goal of this workshop series is to provide a forum for researchers, commercial Internet facilities and service providers, technologists, economists, theorists, policy makers, and other stakeholders to empirically inform emerging Internet regulatory and policy debates.

Presenters were asked to write talk abstracts on their presented topics, addressing four questions:

1. What is the policy goal or fear you’re addressing?
2. What data is needed to measure progress toward/away from this goal fear?
3. What methods do you propose (or are) being used to gather such data?
4. Who/how should such methods be executed, and the data shared, or not shared?

With a specific focus on measurement challenges, the topics we discussed included: analyzing the evolution of the Internet in a layered-platform context to gain new insights; measurement and analysis of economic impacts of new technologies using old tools; security and trustworthiness, reach (universal service) and reachability, sustainability of investment into public Internet infrastructure, as well as infrastructure to measure the public Internet.

Some of the takeaways from the workshop included:
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Presented at our 10th AIMS Workshop earlier this year, the MANIC project resulted in a prototype system to monitor interdomain links and their congestion state to support inference of persistent interdomain congestion. We announce the release of web and API-based methods to access the data. MANIC provides both a graphical user interface for conducting queries and visualizing results and programmatic access to the measurements via a queryable API. We used this MANIC infrastructure and data in our recent publication of “Inferring Persistent Interdomain Congestion”, which won the best paper award at ACM SIGCOMM 2018.

                                                       MANIC dashboard screenshot examples.

Excerpted from the paper:

“(4) We are publicly releasing our analysis scripts, and the underlying datasets via an interactive visualization interface and query API to encourage reproducibility of our results. Our data management system, based on the InfluxDB time-series database and Grafana visualization front-end, allows interactive data exploration, near real-time views of interdomain links, and longitudinal views. While this paper focuses on data from U.S. broadband access providers, we are publicly releasing measurements from VPs outside the U.S. as well.”

For access to the MANIC dashboard, or questions about the publicly accessible API, please contact manic-info@caida.org. (It is a beta prototype, in progress!)

Congratulations to Amogh Dhamdhere, David Clark, Alexander Gamero-Garrido, Matthew Luckie, Ricky K.P. Mok, Gautam Akiwate, Kabir Gogia, Vaibhav Bajpai, Alex Snoeren, and kc claffy, for being awarded Best Paper at SIGCOMM 2018!

The abstract from the paper, “Inferring Persistent Interdomain Congestion“:

There is significant interest in the technical and policy communities regarding the extent,scope, and consumer harm of persistent interdomain congestion. We provide empirical grounding for discussions of interdomain congestion by developing a system and method to measure congestion on thousands of interdomain links without direct access to them. We implement a system based on the Time Series Latency Probes (TSLP) technique that identifies links with evidence of recurring congestion suggestive of an under-provisioned link. We deploy our system at 86 vantage points worldwide and show that congestion inferred using our lightweight TSLP method correlates with other metrics of interconnection performance impairment. We use our method to study interdomain links of eight large U.S. broadband access providers from March 2016 to December 2017, and validate our inferences against ground-truth traffic statistics from two of the providers. For the period of time over which we gathered measurements, we did not find evidence of widespread endemic congestion on interdomain links between access ISPs and directly connected transit and content providers, although some such links exhibited recurring congestion patterns. We describe limitations, open challenges, and a path toward the use of this method for large-scale third-party monitoring of the Internet interconnection ecosystem.

Read the full paper on the CAIDA website.

Detecting Internet outages world-wide and in real-time is no small feat. It requires distributed measurement infrastructure, tools and processing power to analyze the resulting data, plenty of storage to save it, and a powerful user interface to visualize the data. IODA (short for Internet Outage Detection and Analysis) is CAIDA’s solution to this problem.

In an attempt to make IODA more useful, we just launched @caida_ioda, a Twitter account to bring attention to select Internet outages. We inaugurated this account by revealing an outage that took place in Morocco, on July 19, from 11:30 pm to 3:50 am local time. The visualization below illustrates this outage. The blue time series represents our active probing data. This data comes from a cluster of twenty software instances, located at SDSC in San Diego, that repeatedly ping active hosts in the IPv4 address space. Each data point of the time series captures the normalized number of /24 network blocks in Morocco that responded to these pings. The data is normalized with respect to the maximum value observed in the inspected time interval. Starting at 10:20 pm UTC, this fraction dropped significantly (from ~19,700 /24 network blocks to as low as ~13,400) and slowly started to recover after a few hours. The green time series exhibits a drop at the same time—it represents the normalized number of /24 network blocks that are reachable according to BGP, and geolocated to Morocco. The gaps in the BGP time series are due to missing data points caused by temporary issues with our infrastructure. You can use our interactive dashboard to investigate this outage yourself.

Internet outages do not always affect entire countries; their scope is frequently limited to regions or autonomous systems (ASes). IODA can detect such sub-national outages and, coming back to our example, did so for Morocco. The map below suggests that not all of the country’s regions were affected equally. Note, however, that IP address geolocation (that is, the mapping from IP address to geographical location) is far from perfect, so take this information with a grain of salt.

IODA determines an anomaly score for each outage that it detects. Our help page provides more details on how we determine this score but in essence it’s a number that captures the severity of the outage. A look at IODA’s AS-level breakdown confirms that Maroc Telecom was affected the most—the ISP’s overall anomaly score is more than twice that of Itissalat Al-Maghrib, the ISP that ranked second.

So, what happened? IODA reveals where Internet outages happen but it cannot tell us why. Understanding an outage’s root cause still requires a human in the loop; mostly to read news reports and social media postings that mention the outage. In our example, a search of the Arabic-speaking part of the Internet for “morocco internet” led us to Maroc Telecom’s Facebook page, which cited a power outage as the cause:

The time span quoted by Maroc Telecom roughly confirms what IODA saw but our data suggests that the outage began earlier—our active probers first saw a decline in connectivity at 11:30 pm—about half an hour before the alleged start of the outage.

We are supporting public access to IODA’s dashboard for exploration of this and other outages; please use it and send feedback to ioda-info AT caida DOT org.

For the last ten years (with some gaps due to network upgrades), CAIDA has captured monthly traffic samples on Internet backbone links in several large U.S[ cities (San Jose, Chicago, and since March this year, New York City).
We publish statistics for these traces at http://www.caida.org/data/passive/trace_stats/, which illustrates the growth in IPv6 traffic, relative to IPv4. Over the 10-year period covered by our traffic captures, the increase follows a steady exponential trend (linear on a log-lin graph), increasing 10-fold every 3 years. Currently the IPv6 fraction hovers around 1%. Were this trend to continue, the ratios would be roughly 50% each around October 2022 (for packets) September 2023 (for bytes). The byte fraction increases more slowly, reflecting a slightly smaller average IPv6 packet size compared to IPv4.

We are not making any predictions, and note that CGN deployment is also increasing rapidly. We are just reporting the best available data we have.