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Characterizing Geospatial Dynamics of Application Usage in a 3G Cellular Data Network
"... Abstract—Recent studies on cellular network measurement have provided the evidence that significant geospatial correlations, in terms of traffic volume and application access, exist in cellular network usage. Such geospatial correlation patterns provide local optimization opportunities to cellular n ..."
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Abstract—Recent studies on cellular network measurement have provided the evidence that significant geospatial correlations, in terms of traffic volume and application access, exist in cellular network usage. Such geospatial correlation patterns provide local optimization opportunities to cellular network operators for handling the explosive growth in the traffic volume observed in recent years. To the best of our knowledge, in this paper, we provide the first fine-grained characterization of the geospatial dynamics of application usage in a 3G cellular data network. Our analysis is based on two simultaneously collected traces from the radio access network (containing location records) and the core network (containing traffic records) of a tier-1 cellular network in the United States. To better understand the application usage in our data, we first cluster cell locations based on their application distributions and then study the geospatial dynamics of application usage across different geographical regions. The results of our measurement study present cellular network operators with fine-grained insights that can be leveraged to tune network parameter settings. I.
Network Performance of Smart Mobile Handhelds in a University Campus WiFi Network
"... Smart mobile handheld devices (MHDs) such as smartphones have been used for a wide range of applications. Despite the recent flurry of research on various aspects of smart MHDs, little is known about their network performance in WiFi networks. In this paper, we measure the network performance of sma ..."
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Smart mobile handheld devices (MHDs) such as smartphones have been used for a wide range of applications. Despite the recent flurry of research on various aspects of smart MHDs, little is known about their network performance in WiFi networks. In this paper, we measure the network performance of smart MHDs inside a university campus WiFi network, and identify the dominant factors that affect the network performance. Specifically, we analyze 2.9TB of data collected over three days by a monitor that is located at a gateway router of the network, and make the following findings: (1) Compared to non-handheld devices (NHDs), MHDs use well provisioned Akamai and Google servers more heavily, which boosts the overall network performance of MHDs. Furthermore, MHD flows, particularly short flows, benefit from the large initial congestion window that has been adopted by Akamai and Google servers. (2) MHDs tend to have larger local delays inside the WiFi network and are more adversely affected by the number of concurrent flows. (3) Earlier versions of Android OS (before 4.X) cannot take advantage of the large initial congestion window adopted by many servers. On the other hand, the large receive window adopted by iOS is not fully utilized by most flows, potentially leading to waste of resources. (4) Some applicationlevel protocols cause inefficient use of network and operating system resources of MHDs in WiFi networks. Our observations provide valuable insights on content distribution, server provisioning, MHD system design, and applicationlevel protocol design.
AccuLoc: Practical localization of performance measurements in 3G networks
- In ACM MobiSys
, 2011
"... Operators of 3G data networks have to distinguish the performance of each geographic area in their 3G networks to detect and resolve located network problems. This is because the quality of the “last mile ” radio link between 3G base stations and end-user devices is a crucial factor in the end-to-en ..."
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Operators of 3G data networks have to distinguish the performance of each geographic area in their 3G networks to detect and resolve located network problems. This is because the quality of the “last mile ” radio link between 3G base stations and end-user devices is a crucial factor in the end-to-end performance that each user experiences. It is relatively straightforward to measure the performance of all IP traffic in the 3G network from a small number of vantage points in the core network. However, the location information available about each mobile device (e.g., the cell sector/site that it is in) is often too stale to be accurate because of user mobility. Moreover, it is impractical to collect fine-grained location information about all mobile devices on an on-going basis in large 3G networks due to expensive measurement overhead. Thus, it is a challenge to accurately assign IP performance measurements to fine-grained
PROTEUS: Network Performance Forecast for RealTime, Interactive Mobile Applications
- In MobiSys
, 2013
"... Real-time communication (RTC) applications such as VoIP, video conferencing, and online gaming are flourishing. To adapt and deliver good performance, these applications re-quire accurate estimations of short-term network performance metrics, e.g., loss rate, one-way delay, and throughput. How-ever, ..."
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Cited by 9 (1 self)
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Real-time communication (RTC) applications such as VoIP, video conferencing, and online gaming are flourishing. To adapt and deliver good performance, these applications re-quire accurate estimations of short-term network performance metrics, e.g., loss rate, one-way delay, and throughput. How-ever, the wide variation in mobile cellular network perfor-mance makes running RTC applications on these networks problematic. To address this issue, various performance adaptation techniques have been proposed, but one common problem of such techniques is that they only adjust appli-cation behavior reactively after performance degradation is visible. Thus, proactive adaptation based on accurate short-term, fine-grained network performance prediction can be a preferred alternative that benefits RTC applications.
An end-to-end measurement study of modern cellular data networks
- In Proceedings of PAM ’14
, 2014
"... Abstract. With the significant increase in cellular data usage, it is critical to bet-ter understand the characteristics and behavior of cellular data networks. With both laboratory experiments and crowd-sourcing measurements, we investigated the characteristics of the cellular data networks for the ..."
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Abstract. With the significant increase in cellular data usage, it is critical to bet-ter understand the characteristics and behavior of cellular data networks. With both laboratory experiments and crowd-sourcing measurements, we investigated the characteristics of the cellular data networks for the three mobile ISPs in Singa-pore. We found that i) the transmitted packets tend to arrive in bursts; ii) there can be large variations in the instantaneous throughput over a short period of time; iii) large separate downlink buffers are typically deployed, which can cause high la-tency when the throughput is low; and iv) the networks typically implement some form of fair queuing policy. 1
Predicting Handoffs in 3G Networks
"... Cellular data networks have recently seen an explosion in their usage due to the widespread deployment of 3G technologies and the rapid proliferation of smartphones. People are increasingly using their ..."
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Cited by 3 (2 self)
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Cellular data networks have recently seen an explosion in their usage due to the widespread deployment of 3G technologies and the rapid proliferation of smartphones. People are increasingly using their
On the Use of Location Window in Geo-Intelligent HTTP Adaptive Video Streaming
"... Abstract—HTTP adaptive video streaming has become the de facto standard for media data delivery in the Internet. Mobile users are increasingly accessing video streaming services while traveling in fast-moving vehicles (e.g., public transport). The inherent high-speed mobility in these scenarios esca ..."
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Abstract—HTTP adaptive video streaming has become the de facto standard for media data delivery in the Internet. Mobile users are increasingly accessing video streaming services while traveling in fast-moving vehicles (e.g., public transport). The inherent high-speed mobility in these scenarios escalates bandwidth uncertainty and seriously degrades the performance of HTTP adaptive video streaming. This paper proposes a location window based geo-intelligent adaptive streaming algorithm, which adapts to the geo-spatial bandwidth variations experienced by a fast-moving user by adjusting the quality of the next chunk based on the estimated bandwidth at the next X locations of the mobile user. In order to realize geo-intelligence, we introduce a neural network model for accurately creating bandwidth maps that store location-specific bandwidth knowledge. By incorporating both these contributions in conjunction with real-world mobile broadband bandwidth traces from a metropolitan area, we present a systematic study to explore the effects of varying the size of the location window on the user-perceived Quality of Experience (QoE). The evaluation results demonstrate that an optimum location window can be identified, which can almost entirely eliminate playout buffer underruns, thus leading to a smooth and high-quality streaming experience. I.
Mobile Broadband Performance Measured from High-Speed Regional Trains
- In Proc. of the IEEE Vehicular Technology Conference (VTC Fall
, 2011
"... Abstract-While mobile broadband performance measured from moving vehicles in metropolitan areas has drawn significant attentions in recent studies, similar investigations have not been conducted for regional areas. Compared to metropolitan cities, regional suburbs are often serviced by wireless tec ..."
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Abstract-While mobile broadband performance measured from moving vehicles in metropolitan areas has drawn significant attentions in recent studies, similar investigations have not been conducted for regional areas. Compared to metropolitan cities, regional suburbs are often serviced by wireless technologies with significantly lower data rates and less dense deployments. Conversely, vehicle speeds are usually much higher in the regional areas. In this paper, we seek to provide some insights to user experience of mobile broadband in terms of TCP throughput when travelling in a regional train. We find that (1) using a single broadband provider may lead to a large number of blackouts, which could be reduced drastically by simultaneously subscribing to multiple providers (provider blackouts are not highly correlated), (2) the choice of train route may have a more significant effect on broadband experience than the time-of-day of a particular trip, and (3) the speed of the train itself has no deterministic effect on TCP throughput.
In ia d
"... j t-Reuter-net protocol stack. To cater the increasing bandwidth demand, network technolo-gies with higher capacity are introduced both in the wired and wireless Internet. Indeed, in the wired part of the network, we ob-serve an increased adoption of the optical networking technolo-gies, both inside ..."
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j t-Reuter-net protocol stack. To cater the increasing bandwidth demand, network technolo-gies with higher capacity are introduced both in the wired and wireless Internet. Indeed, in the wired part of the network, we ob-serve an increased adoption of the optical networking technolo-gies, both inside the Internet core (i.e., ISP networks) and at the network edges (i.e., fiber at home). A similar trend is observed also in the wireless part of the network, where there is a joint effort of pushing towards this evolution, while the social platforms have an increasing role in the way users access, share and modify the content. The radical departure from the objectives that have driven the original Internet design is now pushing towards a re-design of the Internet architecture and protocols to take into account new design requirements that are outside the original Internet design. Security and privacy is clearly a key requirement, but several other requirements must be taken into account in the Future Internet de-sign, such as supporting users ’ mobility, efficiently handling of multimedia and interactive services, tolerating network partition-ing and/or node disconnections. In particular, energy efficiency is
