469 research outputs found

    Adaptive Video Streaming for Wireless Networks with Multiple Users and Helpers

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    We consider the optimal design of a scheduling policy for adaptive video streaming in a wireless network formed by several users and helpers. A feature of such networks is that any user is typically in the range of multiple helpers. Hence, in order to cope with user-helper association, load balancing and inter-cell interference, an efficient streaming policy should allow the users to dynamically select the helper node to download from, and determine adaptively the video quality level of the download. In order to obtain a tractable formulation, we follow a "divide and conquer" approach: i) Assuming that each video packet (chunk) is delivered within its playback delay ("smooth streaming regime"), the problem is formulated as a network utility maximization (NUM), subject to queue stability, where the network utility function is a concave and componentwise non-decreasing function of the users' video quality measure. ii) We solve the NUM problem by using a Lyapunov Drift Plus Penalty approach, obtaining a scheme that naturally decomposes into two sub-policies referred to as "congestion control" (adaptive video quality and helper station selection) and "transmission scheduling" (dynamic allocation of the helper-user physical layer transmission rates).Our solution is provably optimal with respect to the proposed NUM problem, in a strong per-sample path sense. iii) Finally, we propose a method to adaptively estimate the maximum queuing delays, such that each user can calculate its pre-buffering and re-buffering time in order to cope with the fluctuations of the queuing delays. Through simulations, we evaluate the performance of the proposed algorithm under realistic assumptions of a network with densely deployed helper nodes, and demonstrate the per-sample path optimality of the proposed solution by considering a non-stationary non-ergodic scenario with user mobility, VBR video coding.Comment: final version to appear in IEEE Transactions on Communication

    Fundamental Limits of Caching in Wireless D2D Networks

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    We consider a wireless Device-to-Device (D2D) network where communication is restricted to be single-hop. Users make arbitrary requests from a finite library of files and have pre-cached information on their devices, subject to a per-node storage capacity constraint. A similar problem has already been considered in an ``infrastructure'' setting, where all users receive a common multicast (coded) message from a single omniscient server (e.g., a base station having all the files in the library) through a shared bottleneck link. In this work, we consider a D2D ``infrastructure-less'' version of the problem. We propose a caching strategy based on deterministic assignment of subpackets of the library files, and a coded delivery strategy where the users send linearly coded messages to each other in order to collectively satisfy their demands. We also consider a random caching strategy, which is more suitable to a fully decentralized implementation. Under certain conditions, both approaches can achieve the information theoretic outer bound within a constant multiplicative factor. In our previous work, we showed that a caching D2D wireless network with one-hop communication, random caching, and uncoded delivery, achieves the same throughput scaling law of the infrastructure-based coded multicasting scheme, in the regime of large number of users and files in the library. This shows that the spatial reuse gain of the D2D network is order-equivalent to the coded multicasting gain of single base station transmission. It is therefore natural to ask whether these two gains are cumulative, i.e.,if a D2D network with both local communication (spatial reuse) and coded multicasting can provide an improved scaling law. Somewhat counterintuitively, we show that these gains do not cumulate (in terms of throughput scaling law).Comment: 45 pages, 5 figures, Submitted to IEEE Transactions on Information Theory, This is the extended version of the conference (ITW) paper arXiv:1304.585

    AngelCast: cloud-based peer-assisted live streaming using optimized multi-tree construction

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    Increasingly, commercial content providers (CPs) offer streaming solutions using peer-to-peer (P2P) architectures, which promises significant scalabil- ity by leveraging clients’ upstream capacity. A major limitation of P2P live streaming is that playout rates are constrained by clients’ upstream capac- ities – typically much lower than downstream capacities – which limit the quality of the delivered stream. To leverage P2P architectures without sacri- ficing quality, CPs must commit additional resources to complement clients’ resources. In this work, we propose a cloud-based service AngelCast that enables CPs to complement P2P streaming. By subscribing to AngelCast, a CP is able to deploy extra resources (angel), on-demand from the cloud, to maintain a desirable stream quality. Angels do not download the whole stream, nor are they in possession of it. Rather, angels only relay the minimal fraction of the stream necessary to achieve the desired quality. We provide a lower bound on the minimum angel capacity needed to maintain a desired client bit-rate, and develop a fluid model construction to achieve it. Realizing the limitations of the fluid model construction, we design a practical multi- tree construction that captures the spirit of the optimal construction, and avoids its limitations. We present a prototype implementation of AngelCast, along with experimental results confirming the feasibility of our service.Supported in part by NSF awards #0720604, #0735974, #0820138, #0952145, #1012798 #1012798 #1430145 #1414119. (0720604 - NSF; 0735974 - NSF; 0820138 - NSF; 0952145 - NSF; 1012798 - NSF; 1430145 - NSF; 1414119 - NSF
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