Internet Router-level Topology Research Articles

Vrfinder

Current methods to analyze the Internet's router-level topology with paths collected using traceroute assume that the source address for each router in the path is either an inbound or off-path address on each router. In this work, we show that outbound addresses are common in our Internet-wide traceroute dataset collected by CAIDA's Ark vantage points in January 2020, accounting for 1.7% - 5.8% of the addresses seen at some point before the end of a traceroute. This phenomenon can lead to mistakes in Internet topology analysis, such as inferring router ownership and identifying interdomain links. We hypothesize that the primary contributor to outbound addresses is Layer 3 Virtual Private Networks (L3VPNs), and propose vrfinder, a technique for identifying L3VPN outbound addresses in traceroute collections. We validate vrfinder against ground truth from two large research and education networks, demonstrating high precision (100.0%) and recall (82.1% - 95.3%). We also show the benefit of accounting for L3VPNs in traceroute analysis through extensions to bdrmapIT, increasing the accuracy of its router ownership inferences for L3VPN outbound addresses from 61.5% - 79.4% to 88.9% - 95.5%.

Vrfinder

Current methods to analyze the Internet's router-level topology with paths collected using traceroute assume that the source address for each router in the path is either an inbound or off-path address on each router. In this work, we show that outbound addresses are common in our Internet-wide traceroute dataset collected by CAIDA's Ark vantage points in January 2020, accounting for 1.7% - 5.8% of the addresses seen at some point before the end of a traceroute. This phenomenon can lead to mistakes in Internet topology analysis, such as inferring router ownership and identifying interdomain links. We hypothesize that the primary contributor to outbound addresses is Layer 3 Virtual Private Networks (L3VPNs), and propose vrfinder, a technique for identifying L3VPN outbound addresses in traceroute collections. We validate vrfinder against ground truth from two large research and education networks, demonstrating high precision (100.0%) and recall (82.1% - 95.3%). We also show the benefit of accounting for L3VPNs in traceroute analysis through extensions to bdrmapIT, increasing the accuracy of its router ownership inferences for L3VPN outbound addresses from 61.5% - 79.4% to 88.9% - 95.5%.

Lessons from "a first-principles approach to understanding the internet's router-level topology"

Our main purpose for this editorial is to reiterate the main message that we tried to convey in our SIGCOMM'04 paper but that got largely lost in all the hype surrounding the use of scale-free network models throughout the sciences in the last two decades. That message was that because of (1) the Internet's highly-engineered architecture, (2) a thorough understanding of its component technologies, and (3) the availability of extensive (but typically noisy) measurements, this complex man-made system affords unique opportunities to unambiguously resolve most claims about its properties, structure, and functionality. In the process, we point out the fallacy of popular approaches that consider complex systems such as the Internet from the perspective of disorganized complexity and argue for renewed efforts and increased focus on advancing an "architecture first" view with its emphasis on studying the organized complexity of systems such as the Internet.

Measured impact of crooked traceroute

Data collected using traceroute-based algorithms underpins research into the Internet's router-level topology, though it is possible to infer false links from this data. One source of false inference is the combination of per-flow load-balancing, in which more than one path is active from a given source to destination, and classic traceroute, which varies the UDP destination port number or ICMP checksum of successive probe packets, which can cause per-flow load-balancers to treat successive packets as distinct flows and forward them along different paths. Consequently, successive probe packets can solicit responses from unconnected routers, leading to the inference of false links. This paper examines the inaccuracies induced from such false inferences, both on macroscopic and ISP topology mapping. We collected macroscopic topology data to 365k destinations, with techniques that both do and do not try to capture load balancing phenomena. We then use alias resolution techniques to infer if a measurement artifact of classic traceroute induces a false router-level link. This technique detected that 2.71% and 0.76% of the links in our UDP and ICMP graphs were falsely inferred due to the presence of load-balancing. We conclude that most per-flow load-balancing does not induce false links when macroscopic topology is inferred using classic traceroute. The effect of false links on ISP topology mapping is possibly much worse, because the degrees of a tier-1 ISP's routers derived from classic traceroute were inflated by a median factor of 2.9 as compared to those inferred with Paris traceroute.

Characterizing and modeling the Internet Router-level topology – The hierarchical features and HIR model

In this paper, we seek to understand the properties related with the hierarchical structure of the Internet Router-level topology. We first analyzed the hierarchical features of the Internet Router-level topology with the actual topology measuring data authorized by CAIDA (The Cooperative Association for Internet Data Analysis) Skitter project. Then we analyzed the distribution of the nodes in each shell, the distribution of the edges within the shell and to the higher shells and induced the computing functions. We proposed a new framework for modeling the Internet Router-level topology with the conclusion we have drawn and we implemented the model, HIR model. HIR model was based on the k-core decomposition in order to reveal the hierarchical of the network. The analysis shows that HIR model can reproduce Internet on most properties and has got the hierarchies of network close to that of Internet. The experiments show that HIR model can fully reflect the hierarchy characteristics of the Internet Router-level topology while preserving the power-law distribution on degree.

Model for router-level internet topology based on attribute evolution

Through the analysis of network topology of national Internet Service Provider (ISP), we introduce the concept of "attraction degree". And we point out that the growth of Internet topology should be attributed to interaction between node's own internal and external factors. Considering the effects of both attribute evolution and geographical limit on topology evolution, we propose a new modeling algorithm for Internet router-level topology. By means of power-law and Laplacian eigenvalue, the presented modeling algorithm is proved to be capable to model Internet router-level topology more exactly.

The Study on the Hierarchy of Internet Router-Level Topology

Being a huge system, Internet topology structure is very complex. It can’t be treated as a plane simply, and its hierarchy must be analyzed. We used the k-core decomposition to disentangle the hierarchical structure of Internet Router-level topology. By analyzing the router-lever Internet topology measuring data from CAIDA (The Cooperative Association for Internet Data Analysis) ,we studied the characteristics of the nodes in the inner hierarchy and outer hierarchy respectively. The frequency-degree power law of the nodes which core-ness is lower and the regionally distribution of the nodes which coreness is higher were concluded. At last, the topology of every hierarchy was described by giving their figures. These descriptions can provide a valuable reference for modeling on the Internet topology.

Modeling internet topology dynamics

Despite the large number of papers on network topology modeling and inference, there still exists ambiguity about the real nature of the Internet AS and router level topology. While recent findings have illustrated the inaccuracies in maps inferred from BGP peering and traceroute measurements, existing topology models still produce static topologies, using simplistic assumptions about power law observations and preferential attachment. Today, topology generators are tightly bound to the observed data used to validate them. Given that the actual properties of the Internet topology are not known, topology generators should strive to reproduce the variability that characterizes the evolution of the Internet topology over time. Future topology generators should be able to express the variations in local connectivity that makes today's Internet: peering relationships, internal AS topology and routing policies each changing over time due to failures, maintenance, upgrades and business strategies of the network. Topology generators should capture those dimensions, by allowing a certain level of randomness in the outcome, rather than enforcing structural assumptions as the truths about Internet's evolving structure, which may never be discovered

Improving lookup latency in distributed hash table systems using random sampling

Distributed hash table (DHT) systems are an important class of peer-to-peer routing infrastructures. They enable scalable wide-area storage and retrieval of information, and will support the rapid development of a wide variety of Internet-scale applications ranging from naming systems and file systems to application-layer multicast. DHT systems essentially build an overlay network, but a path on the overlay between any two nodes can be significantly different from the unicast path between those two nodes on the underlying network. As such, the lookup latency in these systems can be quite high and can adversely impact the performance of applications built on top of such systems. In this paper, we discuss a random sampling technique that incrementally improves lookup latency in DHT systems. Our sampling can be implemented using information gleaned from lookups traversing the overlay network. For this reason, we call our approach lookup-parasitic random sampling (LPRS). LPRS converges quickly, and requires relatively few modifications to existing DHT systems. For idealized versions of DHT systems like Chord, Tapestry, and Pastry, we analytically prove that LPRS can result in lookup latencies proportional to the average unicast latency of the network, provided the underlying physical topology has a power-law latency expansion. We then validate this analysis by implementing LPRS in the Chord simulator. Our simulations reveal that LPRS-Chord exhibits a qualitatively better latency scaling behavior relative to unmodified Chord. The overhead of LPRS is one sample per lookup hop in the worst case. Finally, we provide evidence which suggests that the Internet router-level topology resembles power-law latency expansion. This finding implies that LPRS has significant practical applicability as a general latency reduction technique for many DHT systems. This finding is also of independent interest since it might inform the design of latency-sensitive topology models for the Internet.

An empirical evaluation of internet latency expansion

The Internet's latency expansion determines the asymptotic performance of large-scale distributed systems (such as Peer-to-Peer systems), but previous studies on the Internet have defined expansion in terms of router-level hops. In this paper, we empirically determine the Internet's latency expansion characteristics using measurements from two different Internet topology datasets. Our results show that the Internet router-level topology exhibits a power-law latency expansion, in contrast to its exponential expansion rate in terms of hops.

A first-principles approach to understanding the internet's router-level topology

A detailed understanding of the many facets of the Internet's topological structure is critical for evaluating the performance of networking protocols, for assessing the effectiveness of proposed techniques to protect the network from nefarious intrusions and attacks, or for developing improved designs for resource provisioning. Previous studies of topology have focused on interpreting measurements or on phenomenological descriptions and evaluation of graph-theoretic properties of topology generators. We propose a complementary approach of combining a more subtle use of statistics and graph theory with a first-principles theory of router-level topology that reflects practical constraints and tradeoffs. While there is an inevitable tradeoff between model complexity and fidelity, a challenge is to distill from the seemingly endless list of potentially relevant technological and economic issues the features that are most essential to a solid understanding of the intrinsic fundamentals of network topology. We claim that very simple models that incorporate hard technological constraints on router and link bandwidth and connectivity, together with abstract models of user demand and network performance, can successfully address this challenge and further resolve much of the confusion and controversy that has surrounded topology generation and evaluation.

Incrementally improving lookup latency in distributed hash table systems

Distributed hash table (DHT) systems are an important class of peer-to-peer routing infrastructures. They enable scalable wide-area storage and retrieval of information, and will support the rapid development of a wide variety of Internet-scale applications ranging from naming systems and file systems to application-layer multicast. DHT systems essentially build an overlay network, but a path on the overlay between any two nodes can be significantly different from the unicast path between those two nodes on the underlying network. As such, the lookup latency in these systems can be quite high and can adversely impact the performance of applications built on top of such systems.In this paper, we discuss a random sampling technique that incrementally improves lookup latency in DHT systems. Our sampling can be implemented using information gleaned from lookups traversing the overlay network. For this reason, we call our approach lookup-parasitic random sampling (LPRS). LPRS is fast, incurs little network overhead, and requires relatively few modifications to existing DHT systems.For idealized versions of DHT systems like Chord, Tapestry and Pastry, we analytically prove that LPRS can result in lookup latencies proportional to the average unicast latency of the network, provided the underlying physical topology has a power-law latency expansion. We then validate this analysis by implementing LPRS in the Chord simulator. Our simulations reveal that LPRS-Chord exhibits a qualitatively better latency scaling behavior relative to unmodified Chord.Finally, we provide evidence which suggests that the Internet router-level topology resembles power-law latency expansion. This finding implies that LPRS has significant practical applicability as a general latency reduction technique for many DHT systems. This finding is also of independent interest since it might inform the design of latency-sensitive topology models for the Internet.

Topology-informed Internet replica placement

Recently, several studies have looked into the problem of replicated server placement on the Internet. Some of those studies have demonstrated that there exists a replica placement algorithm that can perform within a factor of 1.1–1.5 of the optimal solution. However, this particular greedy algorithm requires detailed knowledge about network topology, and knowledge about expected client locations on the topology. One of these previous studies has also looked at topology-informed replica placement. They consider placing replicas at highly connected nodes in the Autonomous System level graph. In this paper, we extend their work by investigating the performance of topology-informed placement on Internet router-level topology. In our evaluation, we consider approximated policy-based paths, and examine the sensitivity of our results to different client placements. We find that topology-informed replica placement methods can achieve average client latencies which are within a factor of 1.1–1.2 of the greedy algorithm, but only if the placement method is designed carefully.