29,226 research outputs found
A Dynamic Multimedia User-Weight Classification Scheme for IEEE_802.11 WLANs
In this paper we expose a dynamic traffic-classification scheme to support
multimedia applications such as voice and broadband video transmissions over
IEEE 802.11 Wireless Local Area Networks (WLANs). Obviously, over a Wi-Fi link
and to better serve these applications - which normally have strict bounded
transmission delay or minimum link rate requirement - a service differentiation
technique can be applied to the media traffic transmitted by the same mobile
node using the well-known 802.11e Enhanced Distributed Channel Access (EDCA)
protocol. However, the given EDCA mode does not offer user differentiation,
which can be viewed as a deficiency in multi-access wireless networks.
Accordingly, we propose a new inter-node priority access scheme for IEEE
802.11e networks which is compatible with the EDCA scheme. The proposed scheme
joins a dynamic user-weight to each mobile station depending on its outgoing
data, and therefore deploys inter-node priority for the channel access to
complement the existing EDCA inter-frame priority. This provides efficient
quality of service control across multiple users within the same coverage area
of an access point. We provide performance evaluations to compare the proposed
access model with the basic EDCA 802.11 MAC protocol mode to elucidate the
quality improvement achieved for multimedia communication over 802.11 WLANs.Comment: 15 pages, 8 figures, 3 tables, International Journal of Computer
Networks & Communications (IJCNC
'Two-speed' Scotland : patterns and implications of the digital divide in contemporary Scotland
Peer reviewedPublisher PD
Deep Room Recognition Using Inaudible Echos
Recent years have seen the increasing need of location awareness by mobile
applications. This paper presents a room-level indoor localization approach
based on the measured room's echos in response to a two-millisecond single-tone
inaudible chirp emitted by a smartphone's loudspeaker. Different from other
acoustics-based room recognition systems that record full-spectrum audio for up
to ten seconds, our approach records audio in a narrow inaudible band for 0.1
seconds only to preserve the user's privacy. However, the short-time and
narrowband audio signal carries limited information about the room's
characteristics, presenting challenges to accurate room recognition. This paper
applies deep learning to effectively capture the subtle fingerprints in the
rooms' acoustic responses. Our extensive experiments show that a two-layer
convolutional neural network fed with the spectrogram of the inaudible echos
achieve the best performance, compared with alternative designs using other raw
data formats and deep models. Based on this result, we design a RoomRecognize
cloud service and its mobile client library that enable the mobile application
developers to readily implement the room recognition functionality without
resorting to any existing infrastructures and add-on hardware.
Extensive evaluation shows that RoomRecognize achieves 99.7%, 97.7%, 99%, and
89% accuracy in differentiating 22 and 50 residential/office rooms, 19 spots in
a quiet museum, and 15 spots in a crowded museum, respectively. Compared with
the state-of-the-art approaches based on support vector machine, RoomRecognize
significantly improves the Pareto frontier of recognition accuracy versus
robustness against interfering sounds (e.g., ambient music).Comment: 29 page
MONROE-Nettest: A Configurable Tool for Dissecting Speed Measurements in Mobile Broadband Networks
As the demand for mobile connectivity continues to grow, there is a strong
need to evaluate the performance of Mobile Broadband (MBB) networks. In the
last years, mobile "speed", quantified most commonly by data rate, gained
popularity as the widely accepted metric to describe their performance.
However, there is a lack of consensus on how mobile speed should be measured.
In this paper, we design and implement MONROE-Nettest to dissect mobile speed
measurements, and investigate the effect of different factors on speed
measurements in the complex mobile ecosystem. MONROE-Nettest is built as an
Experiment as a Service (EaaS) on top of the MONROE platform, an open dedicated
platform for experimentation in operational MBB networks. Using MONROE-Nettest,
we conduct a large scale measurement campaign and quantify the effects of
measurement duration, number of TCP flows, and server location on measured
downlink data rate in 6 operational MBB networks in Europe. Our results
indicate that differences in parameter configuration can significantly affect
the measurement results. We provide the complete MONROE-Nettest toolset as open
source and our measurements as open data.Comment: 6 pages, 3 figures, submitted to INFOCOM CNERT Workshop 201
On Factors Affecting the Usage and Adoption of a Nation-wide TV Streaming Service
Using nine months of access logs comprising 1.9 Billion sessions to BBC
iPlayer, we survey the UK ISP ecosystem to understand the factors affecting
adoption and usage of a high bandwidth TV streaming application across
different providers. We find evidence that connection speeds are important and
that external events can have a huge impact for live TV usage. Then, through a
temporal analysis of the access logs, we demonstrate that data usage caps
imposed by mobile ISPs significantly affect usage patterns, and look for
solutions. We show that product bundle discounts with a related fixed-line ISP,
a strategy already employed by some mobile providers, can better support user
needs and capture a bigger share of accesses. We observe that users regularly
split their sessions between mobile and fixed-line connections, suggesting a
straightforward strategy for offloading by speculatively pre-fetching content
from a fixed-line ISP before access on mobile devices.Comment: In Proceedings of IEEE INFOCOM 201
Managing ubiquitous eco cities: the role of urban telecommunication infrastructure networks and convergence technologies
A successful urban management system for a Ubiquitous Eco City requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated, transparent and open decision making mechanism and necessary infrastructure and technologies. Rapidly developing information and telecommunication technologies and their platforms in the late 20th Century improves urban management and enhances the quality of life and place. Telecommunication technologies provide an important base for monitoring and managing activities over wired, wireless or fibre-optic networks. Particularly technology convergence creates new ways in which the information and telecommunication technologies are used. The 21st Century is an era where information has converged, in which people are able to access a variety of services, including internet and location based services, through multi-functional devices such as mobile phones and provides opportunities in the management of Ubiquitous Eco Cities. This paper discusses the recent developments in telecommunication networks and trends in convergence technologies and their implications on the management of Ubiquitous Eco Cities and how this technological shift is likely to be beneficial in improving the quality of life and place. The paper also introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for Ubiquitous Eco Cities
Bandwidth extension of narrowband speech
Recently, 4G mobile phone systems have been
designed to process wideband speech signals whose
sampling frequency is 16 kHz. However, most part of
mobile and classical phone network, and current 3G
mobile phones, still process narrowband speech signals
whose sampling frequency is 8 kHz. During next future,
all these systems must be living together. Therefore,
sometimes a wideband speech signal (with a bandwidth up
to 7,2 kHz) should be estimated from an available
narrowband one (whose frequency band is 300-3400 Hz).
In this work, different techniques of audio bandwidth
extension have been implemented and evaluated. First, a
simple non-model-based algorithm (interpolation
algorithm) has been implemented. Second, a model-based
algorithm (linear mapping) have been designed and
evaluated in comparison to previous one. Several CMOS
(Comparison Mean Opinion Score) [6] listening tests show
that performance of Linear Mapping algorithm clearly
overcomes the other one. Results of these tests are very
close to those corresponding to original wideband speech
signal.Postprint (published version
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