781 research outputs found
Why It Takes So Long to Connect to a WiFi Access Point
Today's WiFi networks deliver a large fraction of traffic. However, the
performance and quality of WiFi networks are still far from satisfactory. Among
many popular quality metrics (throughput, latency), the probability of
successfully connecting to WiFi APs and the time cost of the WiFi connection
set-up process are the two of the most critical metrics that affect WiFi users'
experience. To understand the WiFi connection set-up process in real-world
settings, we carry out measurement studies on million mobile users from
representative cities associating with million APs in billion WiFi
sessions, collected from a mobile "WiFi Manager" App that tops the Android/iOS
App market. To the best of our knowledge, we are the first to do such large
scale study on: how large the WiFi connection set-up time cost is, what factors
affect the WiFi connection set-up process, and what can be done to reduce the
WiFi connection set-up time cost. Based on the measurement analysis, we develop
a machine learning based AP selection strategy that can significantly improve
WiFi connection set-up performance, against the conventional strategy purely
based on signal strength, by reducing the connection set-up failures from
to and reducing time costs of the connection set-up
processes by more than times.Comment: 11pages, conferenc
Heterogeneous integration of optical wireless communications within next generation networks
Unprecedented traffic growth is expected in future wireless networks and new
technologies will be needed to satisfy demand. Optical wireless (OW) communication offers vast unused spectrum and high area spectral efficiency. In this work, optical
cells are envisioned as supplementary access points within heterogeneous RF/OW networks. These networks opportunistically offload traffic to optical cells while utilizing
the RF cell for highly mobile devices and devices that lack a reliable OW connection.
Visible light communication (VLC) is considered as a potential OW technology due
to the increasing adoption of solid state lighting for indoor illumination.
Results of this work focus on a full system view of RF/OW HetNets with three primary areas of analysis. First, the need for network densication beyond current RF
small cell implementations is evaluated. A media independent model is developed
and results are presented that provide motivation for the adoption of hyper dense
small cells as complementary components within multi-tier networks. Next, the relationships between RF and OW constraints and link characterization parameters are
evaluated in order to define methods for fair comparison when user-centric channel
selection criteria are used. RF and OW noise and interference characterization techniques are compared and common OW characterization models are demonstrated
to show errors in excess of 100x when dominant interferers are present. Finally,
dynamic characteristics of hyper dense OW networks are investigated in order to optimize traffic distribution from a network-centric perspective. A Kalman Filter model
is presented to predict device motion for improved channel selection and a novel OW
range expansion technique is presented that dynamically alters coverage regions of
OW cells by 50%.
In addition to analytical results, the dissertation describes two tools that have
been created for evaluation of RF/OW HetNets. A communication and lighting
simulation toolkit has been developed for modeling and evaluation of environments
with VLC-enabled luminaires. The toolkit enhances an iterative site based impulse
response simulator model to utilize GPU acceleration and achieves 10x speedup over
the previous model. A software defined testbed for OW has also been proposed
and applied. The testbed implements a VLC link and a heterogeneous RF/VLC
connection that demonstrates the RF/OW HetNet concept as proof of concept
Cabernet: A Content Delivery Network for Moving Vehicles
This paper describes the design, implementation, and evaluation of Cabernet, a system to deliver data to and from moving vehicles using open 802.11 (WiFi) access points encountered opportunistically during travel. Network connectivity in Cabernet is both fleeting (access points are typicallywithin range for a few seconds) and intermittent (because the access points don't provide continuous coverage), and suffers from high packet loss rates over the wireless channel. On the positive side, in the absence of losses, achievable data rates over WiFi can reach many megabits per second. Unfortunately, current protocols don't establish end-to-end connectivity fast enough, don't cope well with intermittent connectivity, and don't handle high packet loss rates well enough to achieve this potential throughput. Cabernet incorporates two new techniques to improve data delivery throughput: QuickWifi, a streamlined client-side process to establish end-to-end connectivity quickly, reducing the mean time to establish connectivity from 12.9 seconds to less than 366 ms and CTP, a transport protocol that distinguishes congestion on the wired portion of the path from losses over the wireless link to reliably and efficiently deliver data to nodes in cars. We have deployed the system on a fleet of 10 taxis, each running several hours per day in the Boston area. Our experiments show that CTP improves throughput by a factor of 2x over TCP and that QuickWifi increases the number of connectionsby a factor of 4x over unoptimized approaches. Thus, Cabernet is perhaps the first practical system capable of delivering data to moving vehicles over existing short-range WiFi radios, with a mean transfer capacity of approximately 38 megabytes/hour per car, or a mean rate of 87 kbit/s
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Your WiFi is leaking: what do your mobile apps gossip about you?
This paper describes how mobile device apps can inadvertently broadcast personal information through their use of wireless networks despite the correct use of encryption. Using a selection of personas we illustrate how app usage can be tied to personal information. Users would likely assume the confidentiality of personal information (including age, religion, sexuality and gender) when using an encrypted network. However, we demonstrate how encrypted traffic pattern analysis can allow a remote observer to infer potentially sensitive data passively and undetectably without any network credentials. Without the ability to read encrypted WiFi traffic directly, we process the limited side-channel data available (timings and frame sizes) to enable remote app detection. These side-channel data measurements are represented as histograms and used to construct a Random Forest classifier capable of accurately identifying mobile apps from the encrypted traffic they cause. The Random Forest algorithm was able to correctly identify apps with a mean accuracy of ∼99% within the training set. The classifier was then adapted to form the core of a detection program that could monitor multiple devices in real-time. Tests in a closed-world scenario showed 84% accuracy and demonstrated the ability to overcome the data limitations imposed by WiFi encryption. Although accuracy suffers greatly (67%) when moving to an open-world scenario, a high recall rate of 86% demonstrates that apps can unwittingly broadcast personal information openly despite using encrypted WiFi. The open-world false positive rate (38% overall, or 72% for unseen activity alone) leaves much room for improvement but the experiment demonstrates a plausible threat nevertheless. Finally, avenues for improvement and the limitations of this approach are identified. We discuss potential applications, strategies to prevent these leaks, and consider the effort required for an observer to present a practical privacy threat to the everyday WiFi user. This paper presents and demonstrates a nuanced and difficult to solve privacy vulnerability that cannot not be mitigated without considerable changes to current- and next-generation wireless communication protocols
A review of smartphones based indoor positioning: challenges and applications
The continual proliferation of mobile devices has encouraged much effort in
using the smartphones for indoor positioning. This article is dedicated to
review the most recent and interesting smartphones based indoor navigation
systems, ranging from electromagnetic to inertia to visible light ones, with an
emphasis on their unique challenges and potential real-world applications. A
taxonomy of smartphones sensors will be introduced, which serves as the basis
to categorise different positioning systems for reviewing. A set of criteria to
be used for the evaluation purpose will be devised. For each sensor category,
the most recent, interesting and practical systems will be examined, with
detailed discussion on the open research questions for the academics, and the
practicality for the potential clients
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