6,702 research outputs found
Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach
This paper proposes a novel energy-efficient multimedia delivery system
called EStreamer. First, we study the relationship between buffer size at the
client, burst-shaped TCP-based multimedia traffic, and energy consumption of
wireless network interfaces in smartphones. Based on the study, we design and
implement EStreamer for constant bit rate and rate-adaptive streaming.
EStreamer can improve battery lifetime by 3x, 1.5x and 2x while streaming over
Wi-Fi, 3G and 4G respectively.Comment: Accepted in ACM Transactions on Multimedia Computing, Communications
and Applications (ACM TOMCCAP), November 201
Seamless Dynamic Adaptive Streaming in LTE/Wi-Fi Integrated Network under Smartphone Resource Constraints
Exploiting both LTE and Wi-Fi links simultaneously enhances the performance of video streaming services in a smartphone. However, it is challenging to achieve seamless and high quality video while saving battery energy and LTE data usage to prolong the usage time of a smartphone. In this paper, we propose REQUEST, a video chunk request policy for Dynamic Adaptive Streaming over HTTP (DASH) in a smartphone, which can utilize both LTE and Wi-Fi. REQUEST enables seamless DASH video streaming with near optimal video quality under given budgets of battery energy and LTE data usage. Through extensive simulation and measurement in a real environment, we demonstrate that REQUEST significantly outperforms other existing schemes in terms of average video bitrate, rebuffering, and resource waste.Peer reviewe
Hybrid Building/Floor Classification and Location Coordinates Regression Using A Single-Input and Multi-Output Deep Neural Network for Large-Scale Indoor Localization Based on Wi-Fi Fingerprinting
In this paper, we propose hybrid building/floor classification and
floor-level two-dimensional location coordinates regression using a
single-input and multi-output (SIMO) deep neural network (DNN) for large-scale
indoor localization based on Wi-Fi fingerprinting. The proposed scheme exploits
the different nature of the estimation of building/floor and floor-level
location coordinates and uses a different estimation framework for each task
with a dedicated output and hidden layers enabled by SIMO DNN architecture. We
carry out preliminary evaluation of the performance of the hybrid floor
classification and floor-level two-dimensional location coordinates regression
using new Wi-Fi crowdsourced fingerprinting datasets provided by Tampere
University of Technology (TUT), Finland, covering a single building with five
floors. Experimental results demonstrate that the proposed SIMO-DNN-based
hybrid classification/regression scheme outperforms existing schemes in terms
of both floor detection rate and mean positioning errors.Comment: 6 pages, 4 figures, 3rd International Workshop on GPU Computing and
AI (GCA'18
QoE de streaming de vídeo em redes veiculares com multihoming
With the ever-increasing interest and availability of vehicular networks, it is important
to study the Quality-of-Experience provided by these networks, which
ultimately determines the general public perception and thus the overall user
adoption. The broad Internet access, the evolution of user equipment, such
as smartphones, tablets and personal computers, and the appearance of services
like Youtube and Netflix, is leading the user content consumption to be
more and more in the form of video streaming. Either motivated by safety or
commercial applications, video streaming in such highly mobile environments
offers multiple challenges.
This dissertation evaluates the QoE of a multihoming communication strategy,
supported simultaneously byWAVE and Wi-Fi, for increasing the reliability and
performance of video streams in these environments. Furthermore, it also investigates
how distinct network functionalities, such as multihoming load balance,
buffering, and network metrics such as throughput and latency affect the
overall QoE observed. The results obtained led to the proposal of a multihoming
load balance policy for video applications based on access technologies,
aiming to improve QoE. The overall results show that QoE improves by 7.5%
using the proposed approach.Com o aumento contínuo do interesse e disponibilidade de redes veiculares,
é importante agora estudar a Qualidade de Experiência fornecida por estas
redes, que fundamentalmente determina a opinião e a percepção do público
geral sobre um dado serviço. O vasto acesso à Internet, a evolução dos equipamentos,
como os telemóveis atuais, tablets e computadores pessoais, e o
aparecimento de serviços como o YouTube e o Netflix, está a fazer com que
o conteúdo mais consumido seja cada vez mais em forma de streaming de
vídeo. Quer seja motivado por aplicações de segurança ou comerciais, o streaming
de vídeo em ambientes altamente móveis levanta vários desafios.
Esta dissertação avalia a Qualidade de Experiência de técnicas de multihoming,
permitindo o uso de diferentes tecnologias de comunicação, como o
WAVE e o Wi-Fi, para aumentar a fiabilidade e desempenho de streams de
vídeo nestes ambientes. Para além disso, investiga também como é que diferentes
mecanismos de rede, como o balanceamento, multihoming e o buffering,
e métricas como a taxa de transferência e latência, afetam a QoE observada.
Os resultados obtidos levaram à proposta de uma política de divisão
de tráfego para aplicações de vídeo baseada em tecnologias de acesso
para situações de multihoming, visando uma melhoria da QoE do utilizador.
Utilizando o método proposto, os resultados mostram que a experiência do
utilizador tem uma melhoria de 7,5%.Mestrado em Engenharia de Computadores e Telemátic
Dashbell: A Low-cost Smart Doorbell System for Home Use
Smart doorbells allow home owners to receive alerts when a visitor is at the
door, see who the guest is, and communicate with the visitor from a smart
device. They greatly improve people's life quality and contribute to the
evolution of smart homes. However, the commercial smart doorbells are quite
expensive, usually cost more than 190 US dollars, which is a substantial
impediment on the pervasiveness of smart doorbells. To solve this problem, we
introduce the Dashbell-a budget smart doorbell system for home use. It connects
a WiFi-enabled device, the Amazon Dash Button, to a network and enables the
home owner to answer the bell triggered by the dash button using a smartphone.
The Dashbell system also enables fast fault detection and diagnosis due to its
distributed framework.Comment: Accepted by IEEE PerCom 201
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