23,815 research outputs found
Evaluación del rendimiento del servicio de videostreaming adaptativo en redes inalámbricas
YouTube Live is one of the most popular services on the Internet, enabling an easy streaming of a live video with acceptable video quality. Thus, understanding user´s perception of this service is of the utmost importance for network operators.
The image Quality delivered and user videoplayback behavior on YouTube Live streaming are important keys to ensure an adequate Quality of Experience (QoE). In this paper, an analytical model, and stacked Bar Graph to estimate the QoE for encrypted YouTube Live service from packet-level data collected in the interfaces of a wireless network is presented. The inputs to the model are Transport Control Protocol (TCP)/Internet Protocol (IP) metrics, from which two Service Key Performance Indicators (S-KPIs) are estimated, namely video quality level (itag) and, videoplayback connection ratio. The model is developed with an experimental platform, consisting of a user terminal agent, a WiFi wireless network, a network-level emulator, a Mitmproxy and a probe software. Model assessment is carried out by comparing S-KPI estimates with measurements from the terminal agent under different network conditions introduced by the network emulator.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech. Ministerio de EconomĂa y Competitividad (Proyecto TEC2015-69982-R, UNMA13-1E-1864), y FEDER
Estimation of urban sensible heat flux using a dense wireless network of observations
The determination of the sensible heat flux over urban terrain is challenging due to irregular surface geometry and surface types. To address this, in 2006-07, a major field campaign (LUCE) took place at the École Polytechnique Fédérale de Lausanne campus, a moderately occupied urban site. A distributed network of 92 wireless weather stations was combined with routine atmospheric profiling, offering high temporal and spatial resolution meteorological measurements. The objective of this study is to estimate the sensible heat flux over the built environment under convective conditions. Calculations were based on Monin-Obukhov similarity for temperature in the surface layer. The results illustrate a good agreement between the sensible heat flux inferred from the thermal roughness length approach and independent calibrated measurements from a scintillometer located inside the urban canopy. It also shows that using only one well-selected station can provide a good estimate of the sensible heat flux over the campus for convective conditions. Overall, this study illustrates how an extensive network of meteorological measurements can be a useful tool to estimate the sensible heat flux in complex urban environment
Localization to Enhance Security and Services in Wi-Fi Networks under Privacy Constraints
Developments of seamless mobile services are faced with two broad challenges, systems security and user privacy - access to wireless systems is highly insecure due to the lack of physical boundaries and, secondly, location based services (LBS) could be used to extract highly sensitive user information. In this paper, we describe our work on developing systems which exploit location information to enhance security and services under privacy constraints. We describe two complimentary methods which we have developed to track node location information within production University Campus Networks comprising of large numbers of users. The location data is used to enhance security and services. Specifically, we describe a method for creating geographic firewalls which allows us to restrict and enhance services to individual users within a specific containment area regardless of physical association. We also report our work on LBS development to provide visualization of spatio-temporal node distribution under privacy considerations
Crowd Counting Through Walls Using WiFi
Counting the number of people inside a building, from outside and without
entering the building, is crucial for many applications. In this paper, we are
interested in counting the total number of people walking inside a building (or
in general behind walls), using readily-deployable WiFi transceivers that are
installed outside the building, and only based on WiFi RSSI measurements. The
key observation of the paper is that the inter-event times, corresponding to
the dip events of the received signal, are fairly robust to the attenuation
through walls (for instance as compared to the exact dip values). We then
propose a methodology that can extract the total number of people from the
inter-event times. More specifically, we first show how to characterize the
wireless received power measurements as a superposition of renewal-type
processes. By borrowing theories from the renewal-process literature, we then
show how the probability mass function of the inter-event times carries vital
information on the number of people. We validate our framework with 44
experiments in five different areas on our campus (3 classrooms, a conference
room, and a hallway), using only one WiFi transmitter and receiver installed
outside of the building, and for up to and including 20 people. Our experiments
further include areas with different wall materials, such as concrete, plaster,
and wood, to validate the robustness of the proposed approach. Overall, our
results show that our approach can estimate the total number of people behind
the walls with a high accuracy while minimizing the need for prior
calibrations.Comment: 10 pages, 14 figure
Impromptu Deployment of Wireless Relay Networks: Experiences Along a Forest Trail
We are motivated by the problem of impromptu or as- you-go deployment of
wireless sensor networks. As an application example, a person, starting from a
sink node, walks along a forest trail, makes link quality measurements (with
the previously placed nodes) at equally spaced locations, and deploys relays at
some of these locations, so as to connect a sensor placed at some a priori
unknown point on the trail with the sink node. In this paper, we report our
experimental experiences with some as-you-go deployment algorithms. Two
algorithms are based on Markov decision process (MDP) formulations; these
require a radio propagation model. We also study purely measurement based
strategies: one heuristic that is motivated by our MDP formulations, one
asymptotically optimal learning algorithm, and one inspired by a popular
heuristic. We extract a statistical model of the propagation along a forest
trail from raw measurement data, implement the algorithms experimentally in the
forest, and compare them. The results provide useful insights regarding the
choice of the deployment algorithm and its parameters, and also demonstrate the
necessity of a proper theoretical formulation.Comment: 7 pages, accepted in IEEE MASS 201
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