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Multimedia delivery in the future internet
The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio
and video are produced, distributed, shared, managed and consumed on-line through various networks,
like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white
paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked
challenges of the Networked Media in the transition to the Future of the Internet.
Internet has evolved and changed the way we work and live. End users of the Internet have been confronted
with a bewildering range of media, services and applications and of technological innovations concerning
media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace
of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more
than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so
regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected
to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising
to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged
that in a near- to mid-term future, the Internet will provide the means to share and distribute (new)
multimedia content and services with superior quality and striking flexibility, in a trusted and personalized
way, improving citizens’ quality of life, working conditions, edutainment and safety.
In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe
network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as
community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of
interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and
innovative applications “on the move”, like virtual collaboration environments, personalised services/
media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content
combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P
networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to
contribute towards such a vision.
Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6)
and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily
contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way
ahead in the area of Content Aware media delivery platforms
In-network quality optimization for adaptive video streaming services
HTTP adaptive streaming (HAS) services allow the quality of streaming video to be automatically adapted by the client application in face of network and device dynamics. Due to their advantages compared to traditional techniques, HAS-based protocols are widely used for over-the-top (OTT) video streaming. However, they are yet to be adopted in managed environments, such as ISP networks. A major obstacle is the purely client-driven design of current HAS approaches, which leads to excessive quality oscillations, suboptimal behavior, and the inability to enforce management policies. Moreover, the provider has no control over the quality that is provided, which is essential when offering a managed service. This article tackles these challenges and facilitates the adoption of HAS in managed networks. Specifically, several centralized and distributed algorithms and heuristics are proposed that allow nodes inside the network to steer the HAS client's quality selection process. The algorithms are able to enforce management policies by limiting the set of available qualities for specific clients. Additionally, simulation results show that by coordinating the quality selection process across multiple clients, the proposed algorithms significantly reduce quality oscillations by a factor of five and increase the average delivered video quality by at least 14%
Analysis domain model for shared virtual environments
The field of shared virtual environments, which also
encompasses online games and social 3D environments, has a
system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model
The AURORA Gigabit Testbed
AURORA is one of five U.S. networking testbeds charged with exploring applications of, and technologies necessary for, networks operating at gigabit per second or higher bandwidths. The emphasis of the AURORA testbed, distinct from the other four testbeds, BLANCA, CASA, NECTAR, and VISTANET, is research into the supporting technologies for gigabit networking.
Like the other testbeds, AURORA itself is an experiment in collaboration, where government initiative (in the form of the Corporation for National Research Initiatives, which is funded by DARPA and the National Science Foundation) has spurred interaction among pre-existing centers of excellence in industry, academia, and government.
AURORA has been charged with research into networking technologies that will underpin future high-speed networks. This paper provides an overview of the goals and methodologies employed in AURORA, and points to some preliminary results from our first year of research, ranging from analytic results to experimental prototype hardware. This paper enunciates our targets, which include new software architectures, network abstractions, and hardware technologies, as well as applications for our work
Models and Methods for Network Selection and Balancing in Heterogeneous Scenarios
The outbreak of 5G technologies for wireless communications can be considered a response to the need for widespread coverage, in terms of connectivity and bandwidth, to guarantee broadband services, such as streaming or on-demand programs offered by the main television networks or new generation services based on augmented and virtual reality (AR / VR).
The purpose of the study conducted for this thesis aims to solve two of the main problems that will occur with the outbreak of 5G, that is, the search for the best possible connectivity, in order to offer users the resources necessary to take advantage of the new generation services, and multicast as required by the eMBMS.
The aim of the thesis is the search for innovative algorithms that will allow to obtain the best connectivity to offer users the resources necessary to use the 5G services in a heterogeneous scenario. Study UF that allows you to improve the search for the best candidate network and to achieve a balance that allows you to avoid congestion of the chosen networks. To achieve these two important focuses, I conducted a study on the main mathematical methods that made it possible to select the network based on QoS parameters based on the type of traffic made by users. A further goal was to improve the computational computation performance they present.
Furthermore, I carried out a study in order to obtain an innovative algorithm that would allow the management of multicast. The algorithm that has been implemented responds to the needs present in the eMBMS, in realistic scenarios
Control of Multiple Remote Servers for Quality-Fair Delivery of Multimedia Contents
This paper proposes a control scheme for the quality-fair delivery of several
encoded video streams to mobile users sharing a common wireless resource. Video
quality fairness, as well as similar delivery delays are targeted among
streams. The proposed controller is implemented within some aggregator located
near the bottleneck of the network. The transmission rate among streams is
adapted based on the quality of the already encoded and buffered packets in the
aggregator. Encoding rate targets are evaluated by the aggregator and fed back
to each remote video server (fully centralized solution), or directly evaluated
by each server in a distributed way (partially distributed solution). Each
encoding rate target is adjusted for each stream independently based on the
corresponding buffer level or buffering delay in the aggregator. Communication
delays between the servers and the aggregator are taken into account. The
transmission and encoding rate control problems are studied with a
control-theoretic perspective. The system is described with a multi-input
multi-output model. Proportional Integral (PI) controllers are used to adjust
the video quality and control the aggregator buffer levels. The system
equilibrium and stability properties are studied. This provides guidelines for
choosing the parameters of the PI controllers. Experimental results show the
convergence of the proposed control system and demonstrate the improvement in
video quality fairness compared to a classical transmission rate fair streaming
solution and to a utility max-min fair approach
Framework for Content Distribution over Wireless LANs
Wireless LAN (also called as Wi-Fi) is dominantly considered as the most pervasive
technology for Intent access. Due to the low-cost of chipsets and support for high data
rates, Wi-Fi has become a universal solution for ever-increasing application space
which includes, video streaming, content delivery, emergency communication,
vehicular communication and Internet-of-Things (IoT).
Wireless LAN technology is defined by the IEEE 802.11 standard. The 802.11
standard has been amended several times over the last two decades, to incorporate the
requirement of future applications. The 802.11 based Wi-Fi networks are
infrastructure networks in which devices communicate through an access point.
However, in 2010, Wi-Fi Alliance has released a specification to standardize direct
communication in Wi-Fi networks. The technology is called Wi-Fi Direct. Wi-Fi
Direct after 9 years of its release is still used for very basic services (connectivity, file
transfer etc.), despite the potential to support a wide range of applications. The reason
behind the limited inception of Wi-Fi Direct is some inherent shortcomings that limit
its performance in dense networks. These include the issues related to topology
design, such as non-optimal group formation, Group Owner selection problem,
clustering in dense networks and coping with device mobility in dynamic networks. Furthermore, Wi-Fi networks also face challenges to meet the growing number of Wi
Fi users. The next generation of Wi-Fi networks is characterized as ultra-dense
networks where the topology changes frequently which directly affects the network
performance. The dynamic nature of such networks challenges the operators to design
and make optimum planifications.
In this dissertation, we propose solutions to the aforementioned problems. We
contributed to the existing Wi-Fi Direct technology by enhancing the group formation
process. The proposed group formation scheme is backwards-compatible and
incorporates role selection based on the device's capabilities to improve network
performance. Optimum clustering scheme using mixed integer programming is
proposed to design efficient topologies in fixed dense networks, which improves
network throughput and reduces packet loss ratio. A novel architecture using
Unmanned Aeriel Vehicles (UAVs) in Wi-Fi Direct networks is proposed for
dynamic networks. In ultra-dense, highly dynamic topologies, we propose cognitive
networks using machine-learning algorithms to predict the network changes ahead of
time and self-configuring the network
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