Diagnosing Path Inflation of Mobile Client Traffic

Zarifis, Kyriakos; Flach, Tobias; Nori, Srikanth; Choffnes, David; Govindan, Ramesh; Katz-Bassett, Ethan; Mao, Z. Morley; Welsh, Matt

doi:10.1007/978-3-319-04918-2_3

Cited by 28 publications

(21 citation statements)

References 12 publications

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“…Some [23,39,15] have related human mobility patterns to AP and base station resource use, and have found [23,39] that the extent of users' physical mobility is low and concentrated among a small number base stations within a provider's network with infrequent visits to other base stations in that network. Zarifis et al [57] characterize metro-level path inflation (rather than mobility itself) experienced by mobile users accessing Google, identifing inter-domain routing, peering, and carrier topology as possible causes. Similarly, other studies have focused on the measured performance (throughput or delay) of WiFi or cellular connections in the wild [37,43,18] but focus on connection performance rather than on mobility itself.…”

Section: Related Workmentioning

confidence: 98%

Towards a quantitative comparison of location-independent network architectures

Gao

Venkataramani

Kurose

et al. 2014

Proceedings of the 2014 ACM Conference on SIGCOMM

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This paper presents a quantitative methodology and results comparing different approaches for location-independent communication. Our approach is empirical and is based on real Internet topologies, routing tables from real routers, and a measured workload of the mobility of devices and content across network addresses today. We measure the extent of network mobility exhibited by mobile devices with a homebrewed Android app deployed on hundreds of smartphones, and measure the network mobility of Internet content from distributed vantage points. We combine this measured data with our quantitative methodology to analyze the different cost-benefit tradeoffs struck by location-independent network architectures with respect to routing update cost, path stretch, and forwarding table size. We find that more than 20% of users change over 10 IP addresses a day, suggesting that mobility is the norm rather than the exception, so intrinsic and efficient network support for mobility is critical. We also find that with purely name-based routing approaches, each event involving the mobility of a device or popular content may result in an update at up to 14% of Internet routers; but, the fraction of impacted routers is much smaller for the long tail of unpopular content. These results suggest that recent proposals for pure name-based networking may be suitable for highly aggregateable content that moves infrequently but may need to be augmented with addressing-assisted approaches to handle device mobility.

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Section: Related Workmentioning

confidence: 98%

Towards a quantitative comparison of location-independent network architectures

Gao

Venkataramani

Kurose

et al. 2014

Proceedings of the 2014 ACM Conference on SIGCOMM

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“…We make anonymized data from MobiPerf publicly available, and will also demo an interactive visualization of the data collected to date (available on the MobiPerf website), adapted from work by Zarifis et al [3].…”

Section: Demonstrationmentioning

confidence: 99%

Demo

Rosen

Yao

Nikravesh

et al. 2014

Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services

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Mobilyzer is an open-source network measurement library that coordinates network measurement tasks among different applications, facilitates measurement task design, and allows for more effective measurement task management than in existing standalone approaches. Unifying various network tasks into one framework greatly simplifies the problem of developing, deploying and managing measurement tasks which may otherwise interfere with one another. An intelligent scheduler, coordinated by a central server, dynamically schedules tasks to run in the background, preserving the user's battery life and respecting limits set by the user on task frequency and data consumption. We will demo MobiPerf, an open-source mobile network measurement tool built using the Mobilyzer library. MobiPerf collects a wide range of network performance data, ranging from the latency and throughput measurements common in existing client-based measurement frameworks, to HTTP loading times for specific URLs, to inferring RRC state configuration parameters and their impact on performance. We will also demo an interface for viewing a large, open dataset of performance data from around the world collected by MobiPerf.

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“…Zarifis et al [14] provide a detailed taxonomy and analysis of path inflation in mobile networks; here we focus on their time evolution and constrain our analysis to only those cases where both latency and throughput were impacted.…”

Section: Inefficient Pathsmentioning

confidence: 99%

Mobile Network Performance from User Devices: A Longitudinal, Multidimensional Analysis

Nikravesh

Choffnes

Katz-Bassett

et al. 2014

Passive and Active Measurement

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Abstract. In the cellular environment, operators, researchers and end users have poor visibility into network performance for devices. Improving visibility is challenging because this performance depends factors that include carrier, access technology, signal strength, geographic location and time. Addressing this requires longitudinal, continuous and large-scale measurements from a diverse set of mobile devices and networks.This paper takes a first look at cellular network performance from this perspective, using 17 months of data collected from devices located throughout the world. We show that (i) there is significant variance in key performance metrics both within and across carriers; (ii) this variance is at best only partially explained by regional and time-of-day patterns; (iii) the stability of network performance varies substantially among carriers. Further, we use the dataset to diagnose the causes behind observed performance problems and identify additional measurements that will improve our ability to reason about mobile network behavior.

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Diagnosing Path Inflation of Mobile Client Traffic

Cited by 28 publications

References 12 publications

Towards a quantitative comparison of location-independent network architectures

Towards a quantitative comparison of location-independent network architectures

Demo

Mobile Network Performance from User Devices: A Longitudinal, Multidimensional Analysis

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