83 research outputs found
Understanding mobile network quality and infrastructure with user-side measurements
No full textMeasurement collection is a primary step towards analyzing and optimizing performance
of a telecommunication service. With an Mobile Broadband (MBB) network,
the measurement process has not only to track the network’s Quality of Service (QoS)
features but also to asses a user’s perspective about its service performance. The later
requirement leads to “user-side measurements” which assist in discovery of performance
issues that makes a user of a service unsatisfied and finally switch to another
network.
User-side measurements also serve as first-hand survey of the problem domain. In
this thesis, we exhibit the potential in the measurements collected at network edge by
considering two well-known approaches namely crowdsourced and distributed testbed-based
measurements. Primary focus is on exploiting crowdsourced measurements
while dealing with the challenges associated with it. These challenges consist of differences
in sampling densities at different parts of the region, skewed and non-uniform
measurement layouts, inaccuracy in sampling locations, differences in RSS readings
due to device-diversity and other non-ideal measurement sampling characteristics. In
presence of heterogeneous characteristics of the user-side measurements we propose
how to accurately detect mobile coverage holes, to devise sample selection process
so to generate a reliable radio map with reduced sample cost, and to identify cellular
infrastructure at places where the information is not public. Finally, the thesis unveils
potential of a distributed measurement test-bed in retrieving performance features
from domains including user’s context, service content and network features, and understanding
impact from these features upon the MBB service at the application layer.
By taking web-browsing as a case study, it further presents an objective web-browsing
Quality of Experience (QoE) model
Web Experience in Mobile Networks: Lessons from Two Million Page Visits
No full textMeasuring and characterizing web page performance is a challenging task.
When it comes to the mobile world, the highly varying technology characteristics coupled with the opaque network configuration make it even more difficult.
Aiming at reproducibility, we present a large scale measurements study of web page performance collected in eleven commercial mobile networks spanning four countries.
We build a dataset of nearly two million web browsing sessions to we shed light on the impact of different web protocols, browsers, and mobile technologies on the web performance.
We find that the impact of mobile broadband access is sizeable.
For example, the median page load time using mobile broadband increases by a third compared to wired access.
Mobility clearly stresses the system, with handover causing the most evident performance penalties.
Contrariwise, our measurements show that the adoption of HTTP/2 and QUIC has practically negligible impact.
Our work highlights the importance of large-scale measurements.
Even with our controlled setup, the complexity of the mobile web ecosystem is challenging to untangle.
For this, we are releasing the dataset as open data for validation and further research.
We also release together with the datasets we collected the scripts we use to produce the analysis we present in the paper. Please use plot_all.sh script to generate the plots in the paper, using the separate scripts from the "scripts" archive.
Should you use any of these resources, please also make an attribution using the following reference (provided here in bibtex format):
@inproceedings{rajiullah2019web,
title={{Web Experience in Mobile Networks: Lessons from Two Million Page Visits}},
author={Rajiullah, Mohammad and Lutu, Andra and Khatouni, Ali Safari and Fida, Mah-Rukh and Mellia, Marco and Brunstrom, Anna and Alay, Ozgu and Alfredsson, Stefan and Mancuso, Vincenzo},
booktitle={The World Wide Web Conference},
pages={1532--1543},
year={2019},
organization={ACM},
address = {San Francisco, CA, USA},
keywords = {Web Experience, HTTP2, QUIC, TCP, Mobile Broadband, Measurements}
}</pre
SURVEY OF HISTORY BASED ROUTING PROTOCOLS IN DELAY TOLERANT NETWORK
No full textFrequent changes in topology and the lack of infrastructure compel disrupted networks to avoid the use of traditional routing protocols. Rather than defining paths towards destinations, the routing tables store access chances of known nodes towards a specific destination. History of a node’s encounter is maintained in three different ways to find out its power of access to the rest of network nodes. The survey paper discusses various routing schemes based on the past encounter patterns of network nodes.Keywords: (Delay Tolerant Network) DTN; routing protocols; history-based routing; frequency; encounter; inter-contact duration; recency
Youthhood
No full textTESTING-GROUND issue 03, Youthhood, examines worlds through youthful eyes, makes evident young ambitions, and questions how we can better empower young people to design cities, landscapes, and a planet that works for them. The issue includes contributions from: Carmel Keren, Jude Daniel Smith, Claire Edwards, Kazeem Kuteyi, Emmanuel Adarkwah, Reza Nik, Dan Cui, Kristofer Cullum-Fernandez, Fida Sassi, Simeon Shtebunaev, Daze Aghaji, Averill Dimabuyu, Sarri Elfaitouri, Rebecca McDonald-Balfour, and Ed Wall.
Rebecca McDonald-Balfour (Author), Jude Daniel Smith (Author), Daze Aghaji (Author), Carmel Keran (Author), Alexis Liu (Author), Dan Cui (Author), Kristofer Cullum-Fernandez (Author), Fida Sassi (Author), Averill Dimabuyu (Author), Ed
Spatial Interpolation based Cellular Coverage Prediction with Crowdsourced Measurements
No full textCoverage prediction has always been of great concern for mobile network operators. Yet the prevalent approach using analytical models assisted by drive testing based measurements is inherently inaccurate and expensive. We consider a promising alternative for coverage mapping involving crowdsourced measurements and spatial interpolation. In particular, we empirically study the accuracy of wide range of spatial interpolation techniques in different scenarios that capture the unique characteristics of crowdsourced measurements (inaccurate locations, sparse and non-uniform measurements, etc.), and find ordinary kriging to be a fairly robust technique
ZipWeave: Towards Efficient and Reliable Measurement based Mobile Coverage Maps
No full textThe accuracy of measurement-driven mobile coverage maps depends on the quality, density and pattern of the signal strength observations. Thus, identifying an efficient measurement data collection methodology is essential, especially when considering the cost associated with the measurement collection approaches (e.g., drive tests, crowd approaches). We propose ZipWeave, a novel measurement data collection and fusion framework for building efficient and reliable measurement-based mobile coverage maps. ZipWeave incorporates a novel nonuniform sampling strategy to achieve reliable coverage maps with reduced sample size. Assuming prior knowledge of the propagation characteristics of the region of interest, we first examine the potential gains of this non-uniform sampling strategy in different cases via a measurement-based statistical analysis methodology; this involves irregular spatial tessellation of the region of interest into sub-regions with internally similar radio propagation characteristics and sampling based on these subregions. We then present a practical form of ZipWeave nonuniform sampling strategy that can be used even without any prior information. In all our evaluations, we show that the ZipWeave non-uniform sampling approach reduces the samples by half compared to the common systematic-random sampling, while maintaining similar accuracy. Moreover, we show that the other key feature of ZipWeave to combine high-quality controlled measurements (that present limited geographic footprint similar to drive tests) with crowdsourced measurements (that cover a wider footprint) leads to more reliable mobile coverage maps overall
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