Mapping Interconnection in the Internet: Colocation, Connectivity and Congestion

Project Summary

As the global Internet expands to satisfy the demands and expectations of an ever-increasing fraction of the world's population, profound changes are occurring in its interconnection structure, traffic dynamics, and the economic and political power of different players in the ecosystem. These changes not only impact network engineering and operations, but also present broader challenges for technology investment, future network design, public policy, and scientific study of the Internet itself. And yet, from both scientific and policy perspectives, the evolving ecosystem is largely uncharted territory.

We will focus our attention on two related transformations of the ecosystem: the emergence of Internet exchanges (IXes) as anchor points in the mesh of interconnection, and the growing role of content providers and Content Delivery Networks (CDNs) as major sources of traffic flowing into the Internet. By some accounts over half the traffic volume in North America now comes from just two content distributors (Youtube and Netflix). This shift constitutes the rise of a new kind of hierarchy in the ecosystem, bringing fundamentally new constraints on existing players who need to manage traffic on their networks to minimize congestion. Evidence of trouble has increased dramatically in the last five years, resulting in tussles among commercial players as well as between the private sector and regulatory bodies, at the expense of users suffering degraded quality of experience.

The proposed research is structured as two foundational tasks and a set of research questions that build on those tasks. First, we will construct a new type of semantically rich Internet map, which will elucidate the role of IXes in facilitating robust and geographically diverse but complex interdomain connectivity. This map will guide our second task: a measurement study of traffic congestion dynamics induced by evolving peering and traffic management practices of CDNs and ISPs. We will use our own measurement infrastructure as well as measurements from four industry collaborators: Akamai, Netflix, Google, and Comcast. Finally, we will use the results of these two tasks to investigate questions related to infrastructure resiliency, scientific modeling, network economics, and public policy.

Project Timeline

Task 1: Create an IX-aware map of the Internet (October 1, 2014 - September 30, 2016). Lead: CAIDA

	Description	Projected Date	Assigned to	Status
Task 1.1: Incorporating IX connectivity into an AS-level Internet map
1.1.1	automate our technique extracting multilateral peering (MLP) links from public route servers at IXPs	May 2015	CAIDA	done
1.1.2	build a colocation database using available data sources (PeeringDB, Euro-IX, Packet Clearing House, published IX member lists and peering matrices)	Sep 2015	CAIDA	done
1.1.3	use colocation database to identify private peering points	Sep 2015	CAIDA/MIT	done
1.1.4	conduct targeted traceroute probing from multiple vantage points: Ark	Year 1	CAIDA	done
1.1.5	conduct targeted traceroute probing from multiple vantage points: Akamai - MIT - targeted traceroute - CoNEXT	Year 1	MIT	done
1.1.6	conduct targeted traceroute probing from multiple vantage points: (periscope)	Year 1	CAIDA	done
1.1.7	conduct targeted traceroute probing from multiple vantage points: RIPE Atlas	Year 2	CAIDA	done
1.1.8	explore techniques to identify IXes not explicitly seen in the path or documented in public databases and peering at them	Year 2	CAIDA
Task 1.2: Enrich AS map annotations
1.2.1	incorporate additional inputs into machine learning classifier of AS graph node types	Year 1	CAIDA	done
1.2.2	improve node classification by using a much larger training data set of ground-truth AS classifications available from PeeringDB	Year 1	CAIDA	done
1.2.3	improve link classification by analyzing geographic trends in observed BGP announcements to infer regional business AS relationships	Year 1	CAIDA	done
1.2.4	improve link classification using insights into region-specific peering behavior extracted from our MLP inferences	Sep 2017	CAIDA	in progress
Task 1.3: Validate the IX-aware map
1.3.1	publish a list of looking glasses hosted at/nearby IXPs and automate querying them to validate the accuracy of our MLP inferences over time	Apr 2016	CAIDA	done
1.3.2	integrate IX-awareness into AS-Rank and collect feedback from network operators	Sep 2015	CAIDA	done
1.3.3	test our classifications of region-specific relationships using the BGP community values with region-specific annotations	Year 1	CAIDA	done
1.3.4	assign a confidence level to each link observed in traceroute data	Year 2	CAIDA
1.3.5	cross-validate inferences from BGP tables, MLP inferences, targeted traceroutes, and published peering matrices	Year 2	CAIDA	done
1.3.6	explore new validation methods combining information from multiple sources to obtain hints about the likely existence of peering links	Year 3	CAIDA

Task 2: Inferring congestion at interconnection points (October 1, 2014 - September 30, 2016). Lead: MIT

	Description	Projected Date	Assigned to	Status
Task 2.1: Conduct delay-based measurements of congestion
2.1.1	collect and analyze time-series of delay measurements	ongoing	CAIDA	done
2.1.2	study diurnal RTT variations along the paths in question	ongoing	CAIDA/MIT	ongoing
2.1.3	identify and analyze manifestations of interesting events	ongoing	CAIDA	ongoing
2.1.4	provide backend for measurements	May 2015	MIT	done
Task 2.2: Conduct throughput-based measurements of congestion
2.2.1	confirm experimentally that a rate-limited TCP download probe (RLTP) can detect congestion from a single test measuring each direction separately	Jul 2016	MIT	in progress
2.2.2	Use cloud-based nodes and Ark nodes as both clients and servers, conduct rate-limited downloads attempting to cross known interconnection points	Aug 2017	MIT
2.2.3	assess difficulty of using tomography to infer likely location of congestion given current measurement infrastructure deployment; make recommendations for improvement	Aug 2017	MIT
2.2.4	collaborate with Google researchers to integrate the results into their open source Model-Based Internet Performance Metrics (MBM) tool	Year 2	MIT
Task 2.3: Conduct passive traffic-based measurements of congestion
2.3.1	analyze CDN per-download data (transfer rate, time of selected file downloads, anonymized source/destination addresses) for evidence of congestion	Year 2	MIT
2.3.2	map discovered congestion onto interconnection paths using binary tomography	Year 2	CAIDA
2.3.3	compare passive download performance with congestion signal from delay-based measurements	Year 2	MIT
2.3.4	after determining paths between the CDN server and the ISP of the client by active probing, infer the presence of congestion based on data provided by CDN	Year 2	MIT
Task 2.4: Validation and automation of congestion-related inferences
2.4.1	automate detection and analysis of congestion in raw data	ongoing	CAIDA/MIT	done
2.4.2	validate congestion inferences using ground truth data provided by collaborating ISPs	ongoing	CAIDA/MIT
2.4.3	cross-validate the three methods (2.1, 2.2, and 2.3) of discovering congestion	ongoing	CAIDA/MIT
2.4.4	automate finding routers along the path of interest and selecting ping targets	Year 1	CAIDA/MIT	in progress
2.4.5	validate congestion inferences using external tools (testing link capacities and identifying bottlenecks) and data sets (TCP tests from M-Lab)	Year 2	CAIDA
2.4.6	explore approaches (using reverse traceroutes, Akamai traceroute data) to detect and resolve asymmetric routes to localize congestion	Year 2	CAIDA

Task 3: Exploring implications for network resiliency, policy, and science (April 1, 2016 - September 30, 2017).

	Description	Projected Date	Assigned to	Status
Task 3.1: Investigate how IXes influence Internet resiliency
3.1.1	assess the importance of certain ASes and AS-links in maintaining global or local reachability	Year 3	CAIDA
3.1.2	consider whether networks tend to connect at multiple IXes in a city/region (for redundancy) or in different regions (for geo-diversity)	Year 2 and 3	CAIDA
3.1.3	characterize the degree to which the loss of a major IX might potentially isolate or impair regions of the Internet	Year 2 and 3	CAIDA
Task 3.2: Study consequences of regional differences in peering behavior
3.2.1	compare topological structure of different countries/regions	Year 2	CAIDA
3.2.2	analyze the extent to which some countries/regions/organizations are essential hubs connecting to the global Internet	Year 3	CAIDA
3.2.3	identify ASes or IXes exercising regional control of Internet infrastructure ("choke points")	Year 3	CAIDA
3.2.4	reveal routing inefficiencies due to peering issues or unavailability of IXes for local interconnection	Year 3	CAIDA
Task 3.3: Inform growing policy concerns such as network transparency, investment incentives, and market power
3.3.1	publish data on the degree and character of the connections between an ISP and the rest of the Internet, including persistent under-provisioning of interconnection links and compare practices across regions;	Year 2 and 3	CAIDA/MIT
3.3.2	define requirements for data disclosures by ISPs under various scenarios	Sep 2016	MIT	done
3.3.3	derive quantitative metrics of market power from our measurements and examine correlations between these new and conventional metrics and the prevalence of observed congestion on the interconnection links	Year 2 and 3	MIT
3.3.4	extend our past modeling work on fair and stable peering settlements to model performance degradations due to congested interconnections	Year 3	CAIDA
Task 3.4: Refine modeling assumptions about Internet topology and routing
3.4.1	produce an AS graph that is an order of magnitude larger than the previous graphs and is both a multi-graph and a hypergraph	Year 3	CAIDA	done
3.4.2	consider significance of commonly used topological characteristics (degree distribution, clustering, assortativity, etc.)	Year 3	CAIDA	done
3.4.3	quantify the prevalence of complex region-specific AS-relationships in the real world	Year 3	CAIDA
3.4.4	quantify the extent of violations to the assumed "valley free, prefer-customer, prefer-peer" routing policy, and the ASes most likely to produce such violations	Year 3	CAIDA
3.4.5	distill relevant statistical properties from the IX-aware map: colocation and peering behavior of different AS types, distributions of the number of physical locations at which two ASes connect, the scope and nature of region-specific business relationships, etc.	Year 3	CAIDA
Task 3.5: Study trends over time in interconnection and performance
3.5.1	develop, maintain, and archive classic data sets to preserve Internet history	Year 3	CAIDA	ongoing
3.5.2	track longitudinal trends in the practices and effects of interconnection	Year 3	CAIDA
3.5.3	capture dynamics and evolution of the interaction between CDNs and IXes	Year 3	CAIDA