Describing and Simulating Internet Routes

Leguay, Jérémie; Latapy, Matthieu; Friedman, Timur; Salamatian, Kavé

doi:10.1007/11422778_53

Cited by 15 publications

(12 citation statements)

References 31 publications

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“…In our data set we found a mean path length of 17.11 hops which is close to 15.57 hops, the mean value for the whole Internet described in [17]. A much more interesting behavior is that we found no correlation between the geographical distance and the path length.…”

Section: Path Length and Geographical Distancesupporting

confidence: 71%

Analysis of internet latency

Noordally

Nicolay

Anelli

et al. 2016

Proceedings of the 12th Asian Internet Engineering Conference

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Internet connectivity is not fairly distributed around the world, in particular for islands or isolated areas. An example, the internet connection of Reunion Island is mainly based on links to France located about 10, 000kms away. This situation generated a particular connection which induced high delays and degraded internet service. Typically, the minimal delay between France and Reunion Island is around 180ms. In this paper, we investigate the performance of the Internet connection by analyzing delay and path properties from and to Reunion Island mapped to continent IPv4 spread. With two experiments, based on 27 local probes and 7, 860, 000 traces, we propose a correlation analyzing between delay and path properties. One particular finding is that the delay is more dependent of the chosen path as the geographical distance, compared to models in literature.

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Section: Path Length and Geographical Distancesupporting

confidence: 71%

Analysis of internet latency

Noordally

Nicolay

Anelli

et al. 2016

Proceedings of the 12th Asian Internet Engineering Conference

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“…We undertake the first large-scale study of the redundancy in Internet routing. A lot of models have been proposed to characterize the routing and traffic in the Internet [15], [16], [17], [18]. Instead of relying on inter-domain routing models, we use an AS path inference algorithm to derive the actual inter-domain paths used in the Internet.…”

Section: Related Workmentioning

confidence: 99%

Geography-based analysis of the Internet infrastructure

Kasiviswanathan

Eidenbenz

Yan

2011

2011 Proceedings IEEE INFOCOM

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Abstract-In this paper, we study some geographic aspects of the Internet. We base our analysis on a large set of geolocated IP hop-level session data (including about 300, 000 backbone routers, 130 million end hosts, and one billion sessions) that we synthesized from a variety of different input sources such as US census data, computer usage statistics, Internet market share data, IP geolocation data sets, CAIDA's Skitter data set for backbone connectivity, and BGP routing tables. We use this model to perform a nationwide and statewide geographic analysis of the Internet. Our main observations are: (1) There is a dominant coast-to-coast pattern in the US Internet traffic. In fact, in many instances even if the end-devices are not near either coast, still the traffic between them takes a long detour through the coasts. (2) More than half of the Internet paths are inflated by 100% or more compared to their corresponding geometric straight-line distance. This circuitousness makes the average ratio between the routing distance and geometric distance big (around 10). (3) The weighted mean hop count is around 5, but the hop counts are very loosely correlated with the distances. The weighted mean AS count (number of ASes traversed) is around 3.

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“…The method based on active probing is described in [6], implemented by CAIDA [8] in the tool iffinder and used in several works [9] [10]. This method consists on sending UDP datagrams from the same host to all the IP addresses that could belong to the same router.…”

Section: Based On Source Ip Address (Mercator)mentioning

confidence: 99%

Techniques for better alias resolution in Internet topology discovery

García-Jiménez

Magaña

Morató

et al. 2009

2009 IFIP/IEEE International Symposium on Integrated Network Management

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One of the challenging problems related with network topology discovery in Internet is the process of IP address alias identification. Topology information is usually obtained from a set of traceroutes that provide IP addresses of routers in the path from a source to a destination. If these traceroutes are repeated between several source/destination pairs we can get a sampling of all IP addresses for crossed routers. In order to generate the topology graph in which each router is a node, it is needed to identify all IP addresses that belong to the same router. In this work we propose improvements over existing methods to obtain alias identification related mainly with the types and options in probing packets.

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Describing and Simulating Internet Routes

Cited by 15 publications

References 31 publications

Analysis of internet latency

Analysis of internet latency

Geography-based analysis of the Internet infrastructure

Techniques for better alias resolution in Internet topology discovery

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