1,343 research outputs found
WiLiTV: A Low-Cost Wireless Framework for Live TV Services
With the evolution of HDTV and Ultra HDTV, the bandwidth requirement for
IP-based TV content is rapidly increasing. Consumers demand uninterrupted
service with a high Quality of Experience (QoE). Service providers are
constantly trying to differentiate themselves by innovating new ways of
distributing content more efficiently with lower cost and higher penetration.
In this work, we propose a cost-efficient wireless framework (WiLiTV) for
delivering live TV services, consisting of a mix of wireless access
technologies (e.g. Satellite, WiFi and LTE overlay links). In the proposed
architecture, live TV content is injected into the network at a few residential
locations using satellite dishes. The content is then further distributed to
other homes using a house-to-house WiFi network or via an overlay LTE network.
Our problem is to construct an optimal TV distribution network with the minimum
number of satellite injection points, while preserving the highest QoE, for
different neighborhood densities. We evaluate the framework using realistic
time-varying demand patterns and a diverse set of home location data. Our study
demonstrates that the architecture requires 75 - 90% fewer satellite injection
points, compared to traditional architectures. Furthermore, we show that most
cost savings can be obtained using simple and practical relay routing
solutions
vSkyConf: Cloud-assisted Multi-party Mobile Video Conferencing
As an important application in the busy world today, mobile video
conferencing facilitates virtual face-to-face communication with friends,
families and colleagues, via their mobile devices on the move. However, how to
provision high-quality, multi-party video conferencing experiences over mobile
devices is still an open challenge. The fundamental reason behind is the lack
of computation and communication capacities on the mobile devices, to scale to
large conferencing sessions. In this paper, we present vSkyConf, a
cloud-assisted mobile video conferencing system to fundamentally improve the
quality and scale of multi-party mobile video conferencing. By novelly
employing a surrogate virtual machine in the cloud for each mobile user, we
allow fully scalable communication among the conference participants via their
surrogates, rather than directly. The surrogates exchange conferencing streams
among each other, transcode the streams to the most appropriate bit rates, and
buffer the streams for the most efficient delivery to the mobile recipients. A
fully decentralized, optimal algorithm is designed to decide the best paths of
streams and the most suitable surrogates for video transcoding along the paths,
such that the limited bandwidth is fully utilized to deliver streams of the
highest possible quality to the mobile recipients. We also carefully tailor a
buffering mechanism on each surrogate to cooperate with optimal stream
distribution. We have implemented vSkyConf based on Amazon EC2 and verified the
excellent performance of our design, as compared to the widely adopted unicast
solutions.Comment: 10 page
Worst-case delay control in multigroup overlay networks
This paper proposes a novel and simple adaptive control algorithm for the effective delay control and resource utilization of end host multicast (EMcast) when the traffic load becomes heavy in a multigroup network with real-time flows constrained by (sigma, rho) regulators. The control algorithm is implemented at the overlay networks and provides more regulations through a novel (sigma, rho, lambda) regulator at each group end host who suffers from heavy input traffic. To our knowledge, it is the first work to incorporate traffic regulators into the end host multicast to control heavy traffic output. Our further contributions include a theoretical analysis and a set of results. We prove the existence and calculate the value of the rate threshold rho* such that for a given set of K groups, when the average rate of traffic entering the group end hosts rho macr > rho*, the ratio of the worst-case multicast delay bound of the proposed (sigma, rho, lambda) regulator over the traditional (sigma, rho) regulator is O(1/Kn) for any integer n. We also prove the efficiency of the novel algorithm and regulator in decreasing worst-case delays by conducting computer simulations
Resource Allocation Frameworks for Network-coded Layered Multimedia Multicast Services
The explosive growth of content-on-the-move, such as video streaming to
mobile devices, has propelled research on multimedia broadcast and multicast
schemes. Multi-rate transmission strategies have been proposed as a means of
delivering layered services to users experiencing different downlink channel
conditions. In this paper, we consider Point-to-Multipoint layered service
delivery across a generic cellular system and improve it by applying different
random linear network coding approaches. We derive packet error probability
expressions and use them as performance metrics in the formulation of resource
allocation frameworks. The aim of these frameworks is both the optimization of
the transmission scheme and the minimization of the number of broadcast packets
on each downlink channel, while offering service guarantees to a predetermined
fraction of users. As a case of study, our proposed frameworks are then adapted
to the LTE-A standard and the eMBMS technology. We focus on the delivery of a
video service based on the H.264/SVC standard and demonstrate the advantages of
layered network coding over multi-rate transmission. Furthermore, we establish
that the choice of both the network coding technique and resource allocation
method play a critical role on the network footprint, and the quality of each
received video layer.Comment: IEEE Journal on Selected Areas in Communications - Special Issue on
Fundamental Approaches to Network Coding in Wireless Communication Systems.
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QoS and QoE Aware N-Screen Multicast Service
The paper focuses on ensuring the quality-of-service (QoS) and quality-of-experience (QoE) requirements of users having heterogeneous devices in a multicast session. QoS parameters such as bit rate, delays, and packet losses are good indicators for optimizing network services but fall short in characterizing user perception (QoE). In N-Screen service, the users have different devices with heterogeneous attributes like screen size, resolution, and access network interface, and the users have different QoE on N-Screen devices with the same QoS parameters. We formulate the objective function of the N-Screen multicast grouping to ensure the minimum user’s QoE with smaller bandwidth requirement. We propose a dynamic user reassignment scheme to maintain and satisfy the QoE by adapting the user’s membership to the varying network conditions. The proposed schemes combine the available bandwidth and multimedia visual quality to ensure the QoS and QoE. In the network architecture, we introduce the functions of the QoS and QoE aware multicast group management and the estimation schemes for the QoS and QoE parameters. The simulation results show that the proposed multicast service ensures the network QoS and guarantees the QoE of users in the varying network conditions
Auction-based Bandwidth Allocation Mechanisms for Wireless Future Internet
An important aspect of the Future Internet is the efficient utilization of
(wireless) network resources. In order for the - demanding in terms of QoS -
Future Internet services to be provided, the current trend is evolving towards
an "integrated" wireless network access model that enables users to enjoy
mobility, seamless access and high quality of service in an all-IP network on
an "Anytime, Anywhere" basis. The term "integrated" is used to denote that the
Future Internet wireless "last mile" is expected to comprise multiple
heterogeneous geographically coexisting wireless networks, each having
different capacity and coverage radius. The efficient management of the
wireless access network resources is crucial due to their scarcity that renders
wireless access a potential bottleneck for the provision of high quality
services. In this paper we propose an auction mechanism for allocating the
bandwidth of such a network so that efficiency is attained, i.e. social welfare
is maximized. In particular, we propose an incentive-compatible, efficient
auction-based mechanism of low computational complexity. We define a repeated
game to address user utilities and incentives issues. Subsequently, we extend
this mechanism so that it can also accommodate multicast sessions. We also
analyze the computational complexity and message overhead of the proposed
mechanism. We then show how user bids can be replaced from weights generated by
the network and transform the auction to a cooperative mechanism capable of
prioritizing certain classes of services and emulating DiffServ and time-of-day
pricing schemes. The theoretical analysis is complemented by simulations that
assess the proposed mechanisms properties and performance. We finally provide
some concluding remarks and directions for future research
Multicast Scheduling and Resource Allocation Algorithms for OFDMA-Based Systems: A Survey
Multicasting is emerging as an enabling technology
for multimedia transmissions over wireless networks to support several groups of users with flexible quality of service (QoS)requirements. Although multicast has huge potential to push the limits of next generation communication systems; it is however one of the most challenging issues currently being addressed. In this survey, we explain multicast group formation and various
forms of group rate determination approaches. We also provide a systematic review of recent channel-aware multicast scheduling and resource allocation (MSRA) techniques proposed for downlink multicast services in OFDMA based systems. We study these enabling algorithms, evaluate their core characteristics, limitations and classify them using multidimensional matrix. We cohesively review the algorithms in terms of their throughput maximization, fairness considerations, performance complexities,
multi-antenna support, optimality and simplifying assumptions. We discuss existing standards employing multicasting and further highlight some potential research opportunities in multicast systems
DecVi: Adaptive Video Conferencing on Open Peer-to-Peer Networks
Video conferencing has become the preferred way of interacting virtually.
Current video conferencing applications, like Zoom, Teams or WebEx, are
centralized, cloud-based platforms whose performance crucially depends on the
proximity of clients to their data centers. Clients from low-income countries
are particularly affected as most data centers from major cloud providers are
located in economically advanced nations. Centralized conferencing applications
also suffer from occasional outages and are embattled by serious privacy
violation allegations. In recent years, decentralized video conferencing
applications built over p2p networks and incentivized through blockchain are
becoming popular. A key characteristic of these networks is their openness:
anyone can host a media server on the network and gain reward for providing
service. Strong economic incentives combined with lower entry barrier to join
the network, makes increasing server coverage to even remote regions of the
world. These reasons, however, also lead to a security problem: a server may
obfuscate its true location in order to gain an unfair business advantage. In
this paper, we consider the problem of multicast tree construction for video
conferencing sessions in open p2p conferencing applications. We propose DecVi,
a decentralized multicast tree construction protocol that adaptively discovers
efficient tree structures based on an exploration-exploitation framework. DecVi
is motivated by the combinatorial multi-armed bandit problem and uses a
succinct learning model to compute effective actions. Despite operating in a
multi-agent setting with each server having only limited knowledge of the
global network and without cooperation among servers, experimentally we show
DecVi achieves similar quality-of-experience compared to a centralized globally
optimal algorithm while achieving higher reliability and flexibility
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