16 research outputs found
Interference charecterisation, location and bandwidth estimation in emerging WiFi networks
Wireless LAN technology based on the IEEE 802.11 standard, commonly referred
to as WiFi, has been hugely successful not only for the last hop access to the Internet
in home, office and hotspot scenarios but also for realising wireless backhaul in mesh
networks and for point -to -point long- distance wireless communication. This success
can be mainly attributed to two reasons: low cost of 802.11 hardware from reaching
economies of scale, and operation in the unlicensed bands of wireless spectrum.The popularity of WiFi, in particular for indoor wireless access at homes and offices,
has led to significant amount of research effort looking at the performance issues
arising from various factors, including interference, CSMA/CA based MAC protocol
used by 802.11 devices, the impact of link and physical layer overheads on application
performance, and spatio-temporal channel variations. These factors affect the performance
of applications and services that run over WiFi networks. In this thesis, we
experimentally investigate the effects of some of the above mentioned factors in the
context of emerging WiFi network scenarios such as multi- interface indoor mesh networks,
802.11n -based WiFi networks and WiFi networks with virtual access points
(VAPs). More specifically, this thesis comprises of four experimental characterisation
studies: (i) measure prevalence and severity of co- channel interference in urban WiFi
deployments; (ii) characterise interference in multi- interface indoor mesh networks;
(iii) study the effect of spatio-temporal channel variations, VAPs and multi -band operation
on WiFi fingerprinting based location estimation; and (iv) study the effects of
newly introduced features in 802.11n like frame aggregation (FA) on available bandwidth
estimation.With growing density of WiFi deployments especially in urban areas, co- channel
interference becomes a major factor that adversely affects network performance. To
characterise the nature of this phenomena at a city scale, we propose using a new measurement
methodology called mobile crowdsensing. The idea is to leverage commodity
smartphones and the natural mobility of people to characterise urban WiFi co- channel
interference. Specifically, we report measurement results obtained for Edinburgh, a
representative European city, on detecting the presence of deployed WiFi APs via the
mobile crowdsensing approach. These show that few channels in 2.4GHz are heavily
used and there is hardly any activity in the 5GHz band even though relatively it
has a greater number of available channels. Spatial analysis of spectrum usage reveals
that co- channel interference among nearby APs operating in the same channel
can be a serious problem with around 10 APs contending with each other in many locations. We find that the characteristics of WiFi deployments at city -scale are similar
to those of WiFi deployments in public spaces of different indoor environments. We
validate our approach in comparison with wardriving, and also show that our findings
generally match with previous studies based on other measurement approaches. As
an application of the mobile crowdsensing based urban WiFi monitoring, we outline a
cloud based WiFi router configuration service for better interference management with
global awareness in urban areas.For mesh networks, the use of multiple radio interfaces is widely seen as a practical
way to achieve high end -to -end network performance and better utilisation of
available spectrum. However this gives rise to another type of interference (referred to
as coexistence interference) due to co- location of multiple radio interfaces. We show
that such interference can be so severe that it prevents concurrent successful operation
of collocated interfaces even when they use channels from widely different frequency
bands. We propose the use of antenna polarisation to mitigate such interference and
experimentally study its benefits in both multi -band and single -band configurations. In
particular, we show that using differently polarised antennas on a multi -radio platform
can be a helpful counteracting mechanism for alleviating receiver blocking and adjacent
channel interference phenomena that underlie multi -radio coexistence interference.
We also validate observations about adjacent channel interference from previous
studies via direct and microscopic observation of MAC behaviour.Location is an indispensable information for navigation and sensing applications.
The rapidly growing adoption of smartphones has resulted in a plethora of mobile
applications that rely on position information (e.g., shopping apps that use user position
information to recommend products to users and help them to find what they want
in the store). WiFi fingerprinting is a popular and well studied approach for indoor
location estimation that leverages the existing WiFi infrastructure and works based on
the difference in strengths of the received AP signals at different locations. However,
understanding the impact of WiFi network deployment aspects such as multi -band
APs and VAPs has not received much attention in the literature. We first examine the
impact of various aspects underlying a WiFi fingerprinting system. Specifically, we
investigate different definitions for fingerprinting and location estimation algorithms
across different indoor environments ranging from a multi- storey office building to
shopping centres of different sizes. Our results show that the fingerprint definition
is as important as the choice of location estimation algorithm and there is no single
combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz
and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with
WiFi fingerprinting. Our results demonstrate that lower co- channel interference in the
5GHz band yields more accurate location estimation. We show that the inclusion of
VAPs has a significant impact on the location accuracy of WiFi fingerprinting systems;
we analyse the potential reasons to explain the findings.End -to -end available bandwidth estimation (ABE) has a wide range of uses, from
adaptive application content delivery, transport-level transmission rate adaptation and
admission control to traffic engineering and peer node selection in peer -to- peer /overlay
networks [ 1, 2]. Given its importance, it has been received much research attention in
both wired data networks and legacy WiFi networks (based on 802.11 a/b /g standards),
resulting in different ABE techniques and tools proposed to optimise different criteria
and suit different scenarios. However, effects of new MAC/PHY layer enhancements
in new and next generation WiFi networks (based on 802.11n and 802.11ac
standards) have not been studied yet. We experimentally find that among different
new features like frame aggregation, channel bonding and MIMO modes (spacial division
multiplexing), frame aggregation has the most harmful effect as it has direct
effect on ABE by distorting the measurement probing traffic pattern commonly used
to estimate available bandwidth. Frame aggregation is also specified in both 802.11n
and 802.1 lac standards as a mandatory feature to be supported. We study the effect of
enabling frame aggregation, for the first time, on the performance of the ABE using an
indoor 802.11n wireless testbed. The analysis of results obtained using three tools -
representing two main Probe Rate Model (PRM) and Probe Gap Model (PGM) based
approaches for ABE - led us to come up with the two key principles of jumbo probes
and having longer measurement probe train sizes to counter the effects of aggregating
frames on the performance of ABE tools. Then, we develop a new tool, WBest+ that
is aware of the underlying frame aggregation by incorporating these principles. The
experimental evaluation of WBest+ shows more accurate ABE in the presence of frame
aggregation.Overall, the contributions of this thesis fall in three categories - experimental
characterisation, measurement techniques and mitigation/solution approaches for performance
problems in emerging WiFi network scenarios. The influence of various factors
mentioned above are all studied via experimental evaluation in a testbed or real - world setting. Specifically, co- existence interference characterisation and evaluation
of available bandwidth techniques are done using indoor testbeds, whereas characterisation of urban WiFi networks and WiFi fingerprinting based location estimation are
carried out in real environments. New measurement approaches are also introduced
to aid better experimental evaluation or proposed as new measurement tools. These
include mobile crowdsensing based WiFi monitoring; MAC/PHY layer monitoring of
co- existence interference; and WBest+ tool for available bandwidth estimation. Finally,
new mitigation approaches are proposed to address challenges and problems
identified throughout the characterisation studies. These include: a proposal for crowd - based interference management in large scale uncoordinated WiFi networks; exploiting
antenna polarisation diversity to remedy the effects of co- existence interference
in multi -interface platforms; taking advantage of VAPs and multi -band operation for
better location estimation; and introducing the jumbo frame concept and longer probe
train sizes to improve performance of ABE tools in next generation WiFi networks
Inferring Person-to-person Proximity Using WiFi Signals
Today's societies are enveloped in an ever-growing telecommunication
infrastructure. This infrastructure offers important opportunities for sensing
and recording a multitude of human behaviors. Human mobility patterns are a
prominent example of such a behavior which has been studied based on cell phone
towers, Bluetooth beacons, and WiFi networks as proxies for location. However,
while mobility is an important aspect of human behavior, understanding complex
social systems requires studying not only the movement of individuals, but also
their interactions. Sensing social interactions on a large scale is a technical
challenge and many commonly used approaches---including RFID badges or
Bluetooth scanning---offer only limited scalability. Here we show that it is
possible, in a scalable and robust way, to accurately infer person-to-person
physical proximity from the lists of WiFi access points measured by smartphones
carried by the two individuals. Based on a longitudinal dataset of
approximately 800 participants with ground-truth interactions collected over a
year, we show that our model performs better than the current state-of-the-art.
Our results demonstrate the value of WiFi signals in social sensing as well as
potential threats to privacy that they imply
Developing a Systematic Process for Mobile Surveying and Analysis of WLAN security
Wireless Local Area Network (WLAN), familiarly known as Wi-Fi, is one of the most used wireless networking technologies. WLANs have rapidly grown in popularity since the release of the original IEEE 802.11 WLAN standard in 1997. We are using our beloved wireless internet connection for everything and are connecting more and more devices into our wireless networks in every form imaginable. As the number of wireless network devices keeps increasing, so does the importance of wireless network security.
During its now over twenty-year life cycle, a multitude of various security measures and protocols have been introduced into WLAN connections to keep our wireless communication secure. The most notable security measures presented in the 802.11 standard have been the encryption protocols Wired Equivalent Privacy (WEP) and Wi-Fi Protected Access (WPA). Both encryption protocols have had their share of flaws and vulnerabilities, some of them so severe that the use of WEP and the first generation of the WPA protocol have been deemed irredeemably broken and unfit to be used for WLAN encryption. Even though the aforementioned encryption protocols have been long since deemed fatally broken and insecure, research shows that both can still be found in use today.
The purpose of this Masterâs Thesis is to develop a process for surveying wireless local area networks and to survey the current state of WLAN security in Finland. The goal has been to develop a WLAN surveying process that would at the same time be efficient, scalable, and easily replicable. The purpose of the survey is to determine to what extent are the deprecated encryption protocols used in Finland. Furthermore, we want to find out in what state is WLAN security currently in Finland by observing the use of other WLAN security practices. The survey process presented in this work is based on a WLAN scanning method called Wardriving. Despite its intimidating name, wardriving is simply a form of passive wireless network scanning. Passive wireless network scanning is used for collecting information about the surrounding wireless networks by listening to the messages broadcasted by wireless network devices.
To collect our research data, we conducted wardriving surveys on three separate occasions between the spring of 2019 and early spring of 2020, in a typical medium-sized Finnish city. Our survey results show that 2.2% out of the located networks used insecure encryption protocols and 9.2% of the located networks did not use any encryption protocol. While the percentage of insecure networks is moderately low, we observed during our study that private consumers are reluctant to change the factory-set default settings of their wireless network devices, possibly exposing them to other security threats
Passive Radiolocation of IEEE 802.11 Emitters using Directional Antennae
Low-cost commodity hardware and cheaper, more capable consumer-grade drones make the threat of home-made, inexpensive drone-mounted wireless attack platforms (DWAPs) greater than ever. Fences and physical security do little to impede a drone from approaching private, commercial, or government wireless access points (WAPs) and conducting wireless attacks. At the same time, unmanned aerial vehicles (UAVs) present a valuable tool for network defenders conducting site surveys and emulating threats. These platforms present near-term dangers and opportunities for corporations and governments. Despite the vast leaps in technology these capabilities represent, UAVs are noisy and consequently difficult to conceal as they approach a potential target; stealth is a valuable asset to an attacker. Using a directional antenna instead of the typical omnidirectional antenna would significantly increase the distance from which a DWAP may conduct attacks and would improve their stealthiness and overall effectiveness. This research seeks to investigate the possibility of using directional antennae on DWAPs by resolving issues inhibiting directional antennae use on consumer and hobbyist drone platforms. This research presents the hypothesis that a DWAP equipped with a directional antenna can predict bearings and locations of WAPs within an acceptable margin of error
Understanding the interplay between social and spatial behaviour
According to personality psychology, personality traits determine many aspects of human behaviour. However, validating this insight in large groups has been challenging so far, due to the scarcity of multi-channel data. Here, we focus on the relationship between mobility and social behaviour by analysing trajectories and mobile phone interactions of âŒ1000 individuals from two high-resolution longitudinal datasets. We identify a connection between the way in which individuals explore new resources and exploit known assets in the social and spatial spheres. We show that different individuals balance the exploration-exploitation trade-off in different ways and we explain part of the variability in the data by the big five personality traits. We point out that, in both realms, extraversion correlates with the attitude towards exploration and routine diversity, while neuroticism and openness account for the tendency to evolve routine over long time-scales. We find no evidence for the existence of classes of individuals across the spatio-social domains. Our results bridge the fields of human geography, sociology and personality psychology and can help improve current models of mobility and tie formation
Understanding mobile network quality and infrastructure with user-side measurements
Measurement 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 networkâs Quality of Service (QoS)
features but also to asses a userâs perspective about its service performance. The later
requirement leads to âuser-side measurementsâ 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 userâs 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
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Robust, Resilient Networked Communication in Challenged Environments
In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication