Passive and Active Measurement: 15th International by Michalis Faloutsos, Aleksandar Kuzmanovic

By Michalis Faloutsos, Aleksandar Kuzmanovic

This e-book constitutes the refereed court cases of the fifteenth foreign convention on Passive and energetic dimension, PAM 2014, held in la, CA, united states, in 2014. The 24 revised complete papers awarded have been rigorously reviewed and chosen from seventy six submissions. The papers were geared up within the following topical sections: net instant and mobility; dimension layout, adventure and research; functionality size; protocol and alertness habit; characterization of community habit; and community safeguard and privateness. moreover 7 poster papers were included.

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Additional info for Passive and Active Measurement: 15th International Conference, PAM 2014, Los Angeles, CA, USA, March 10-11, 2014, Proceedings

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3 Dataset Data Collected. Our data consists of network measurements (ping, traceroute, HTTP GET, UDP bursts and DNS lookups) issued from Speedometer, an internal Android app developed by Google and deployed on thousands of volunteer devices. Speedometer 26 K. Zarifis et al. 1 Our analysis focuses on measurements toward Google servers including 310K traceroutes, 300K pings and 350K DNS lookups issued in three three-month periods (2011 Q4, 2012 Q2 and Q4). We focus on measurements issued by devices in the US, where the majority of users is located, with a particular density of measurements in areas with large Google offices.

If a carrier’s access network ingresses into the Internet in metro-area L, a lack of peering between the mobile carrier and Google in metroarea L causes traffic to leave the metro area, resulting in Interdomain Inflation (Fig. 2, user C). If a carrier has too few ingresses and lacks peering near its ingresses, we may observe Carrier Access-Interdomain Inflation. In this case a carrier, lacking ingress in area L, hauls traffic to a remote area R, where it lacks peering with Google. A peering point exists in area L, so traffic returns there to enter Google’s network.

2 Mbps downstream HSPA networks. 3 Variations in Mobile Data Network Throughput We now present our findings on the variations in the networks that we investigated. In Fig. 5, we plot the cumulative distribution of the crowd-sourced data obtained from ISPCheck. As expected, HSPA+ networks are generally faster than HSPA networks. 2 Mbps. Overall, we see significant asymmetry in the upstream and downstream data rates and also that the actual throughput achieved by the local subscribers can vary significantly from a few Kbps to several Mbps.

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