Detecting if LTE is the Bottleneck with BurstTracker

Balasingam, Arjun; Bansal, Manu; Misra, Rakesh R.; Nagaraj, Kanthi; Tandra, Rahul; Schulman, Aaron

doi:10.1145/3300061.3300140

Cited by 26 publications

(14 citation statements)

References 29 publications

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“…QXDM [31] and MobileInsight [25] are tools that measure only the PRB allocation of a single user, but not the bandwidth usage of the whole cell, resulting in significant errors in capacity estimation. Systems built atop of MobileInsight, including CLAW [39], PERCEIVE [24] and BurstTracker [7] suffers from the same limitation.…”

Section: Related Workmentioning

confidence: 99%

“…To further demonstrate the advantage of NG-Scope's complete cell-wide information over the partial information MobileInsight [25] observes, we compare NG-Scope with two systems built atop of MobileInsight: CLAW [39] for capacity tracking ( §5.8) and BurstTracker [7] for bottleneck determination ( §5.9). Experimental results show that NG-Scope achieves superior performance compared to these two systems.…”

Section: Introductionmentioning

confidence: 99%

“…Resource allocation results measured using NG-Scope. (a) The cell shares the PRBs inside each subframe (represented by a single bar)among multiple backlogged users, so BurstTracker[7] detects no saturation when it in fact exists; (b) when the user is web browsing, Burst-Tracker indicates long periods of saturation even when the link is not fully saturated.…”

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confidence: 99%

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NG-Scope

Xie

Jamieson

2022

Proc. ACM Meas. Anal. Comput. Syst.

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Accurate and highly-granular channel capacity telemetry of the cellular last hop is crucial for the effective operation of transport layer protocols and cutting edge applications, such as video on demand and video telephony. This paper presents the design, implementation, and experimental performance evaluation of NG-Scope, the first such telemetry tool able to fuse physical-layer channel occupancy readings from the cellular control channel with higher-layer packet arrival statistics and make accurate capacity estimates. NG-Scope handles the latest cellular innovations, such as when multiple base stations aggregate their signals together to serve mobile users. End-to-end experiments in a commercial cellular network demonstrate that wireless capacity varies significantly with channel quality, mobility, competing traffic within each cell, and the number of aggregated cells. Our experiments demonstrate significantly improved cell load estimation accuracy, missing the detection of less than 1% of data capacity overall, a reduction of 82% compared to OWL, the state-of-the-art in cellular monitoring. Further experiments show that MobileInsight-based CLAW has a root-mean-squared capacity error of 30.5 Mbit/s, which is 3.3× larger than NG-Scope (9.2 Mbit/s).

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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NG-Scope

Xie

Jamieson

2022

Proc. ACM Meas. Anal. Comput. Syst.

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“…LTE supports peak down-link bitrate of 300 Mbps, almost 10 times more than over 3G [12]. However, most of the studies show QoE is still unsatisfactory [13]. New applications of video over mobile client are getting popular [14].…”

Section: A Motivation: Why We Need Abr Solutions For Wireless Network?mentioning

confidence: 99%

Adaptive Bitrate Video Streaming for Wireless nodes: A Survey

Nishat,

Gnawali,

Abdelhadi

2020

Preprint

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In today's Internet, video is the most dominant application and in addition to this, wireless networks such as WiFi, Cellular, and Bluetooth have become ubiquitous. Hence, most of the Internet traffic is video over wireless nodes. There is a plethora of research to improve video streaming to achieve high Quality of Experience (QoE) over the Internet. Many of them focus on wireless nodes. Recent measurement studies often show QoE of video suffers in many wireless clients over the Internet. Recently, many research papers have presented models and schemes to optimize the Adaptive BitRate (ABR) based video streaming for wireless and mobile users. In this survey, we present a comprehensive overview of recent work in the area of Internet video specially designed for wireless network. Recent research has suggested that there are some new challenges added by the connectivity of clients through wireless. Also these challenges become more difficult to handle when these nodes are mobile. This survey also discusses new potential areas of future research due to the increasing scarcity of wireless spectrum.

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“…Similar to OWL, FALCON decodes only locations with a sufficient signal power in all covered CCEs and checks the coherence between the candidate's RNTI and the corresponding search space. It also keeps track of any RAR messages that contain RNTI assignments for newly joined UEs which are immediately added to (1,2). Checked locations without any known RNTI (3) are split into two halves and are examined recursively with L/2 (4,5).…”

Section: B Real-time Decodermentioning

confidence: 99%

FALCON: An Accurate Real-Time Monitor for Client-Based Mobile Network Data Analytics

Falkenberg

Wietfeld

2019

2019 IEEE Global Communications Conference (GLOBECOM)

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Network data analysis is the fundamental basis for the development of methods to increase service quality in mobile networks. This requires accurate data of the current load in the network. The control channel analysis is a way to monitor the resource allocations and the throughput of all active subscribers in a public mobile radio cell. Previous open-source approaches require either ideal radio conditions or long-term observations in order to obtain reliable data. Otherwise, the revealed information is polluted by spurious assignments with random content. In this paper, we present a new open-source instrument for Fast Analysis of LTE Control channels (FALCON), which combines a novel shortcut-decoding approach with the most reliable techniques known to us to reduce the aforementioned requirements significantly. Long-term field measurements reveal that FALCON reduces errors in average by three orders of magnitude compared to currently the best approach. FALCON allows observations at locations with interference and enables mobile applications with single short-term tracking of the local load situation. It is compatible with numerous software defined radios and can be used on standard computers for a reliable real-time analysis.

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Detecting if LTE is the Bottleneck with BurstTracker

Cited by 26 publications

References 29 publications

NG-Scope

NG-Scope

Adaptive Bitrate Video Streaming for Wireless nodes: A Survey

FALCON: An Accurate Real-Time Monitor for Client-Based Mobile Network Data Analytics

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