Pouya Ostovari and Jie Wu Computer and Information Sciences

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Presentation transcript:

Robust Wireless Delivery of Scalable Videos using Inter-layer Network Coding Pouya Ostovari and Jie Wu Computer and Information Sciences Temple University Center for Networked Computing http://www.cnc.temple.edu

Agenda Introduction Robustness multi-layer video streaming Evaluations Multi-layer video coding Robustness multi-layer video streaming Evaluations Conclusions First I will provide an introduction and motivation for our work Then, I will talk about the benefits on network coding in robustness and throughput enhancement, and I will talk about our partial results and future work. At the end, I will conclude my talk

Introduction Advances in technology Smartphones and tablets Internet is accessible everywhere Video streaming is used widely and frequently Video streaming is a dominant form of traffic on the Internet YouTube and Netflix: Produce 20-30% of the web traffic on the Internet In recent days, we are witnessing a fast development in the hardware technologies of mobile devices such as tablets and smartphones As a result of these advances, the mobile devices are becoming very popular Using wireless connections is more convenient than the wired connections. Moreover, they can solve the last mile problem

Introduction A challenge in multicasting Scalable video coding Different link conditions Loss rate, bandwidth Scalable video coding Delivering video stream using different resolutions to satisfy different client needs/constraints Scalable videos are useful in delivering video stream with different resolutions to users with different needs There are two forms of scalable videos Multi-layer and multi-description coding Multi-Layer Coding Base layer Enhancement layers

Multi-Layer Video Streaming H.264/SVC coded Temporal layers Quality layers Spatio layers Quality layer 2 Quality layer 1 Unequal error protection Grouping the packets of multiple GOP together Providing different levels of protection for different groups Intra-layer network coding Different heuristics are proposed They focus on measuring the effect of each layer on the video quality Temporal H.264/MPEG-4 or advanced video coding (AVC) is a video compression format It is one of the most commonly used formats for compression and distribution of video content H.264/SVC, which is an extension of the H.264/AVC, supports spatial, temporal, and quality scalabilities GOP is a group of successive pictures within a coded video stream

Inter-Layer Coding Strategies Random linear network coding (RLNC) Triangular coding Prefix coding If a user receives enough coded packets, it can decode and retrive all of the layers Otherwise, it will not be able to decode any layer. Because of this problem, a modification on RLNC is prosed, called triangular network coding Packets in lower layers are more important Included in more coded layers More chance to be decoded

Advantage of Triangular Coding Coefficients are not shown for simplicity 6 transmissions in round-robin pattern Blue cells are received Unable to decode No coding L1 L2 L3 L1 L2 L3 Random linear coding Unable to decode L1 + L2+ L3 L1 + L2+ L3 L1 + L2+ L3 L1 + L2+ L3 L1 + L2+ L3 L1 + L2+ L3 Triangular coding Decodes 2 layers L1 L1 + L2 L1 + L2+ L3 L1 L1 + L2 L1 + L2+ L3

Two-Dimensional Inter-Layer NC Performing inter-layer triangular NC on quality and temporal layers

Two-Dimensional Inter-Layer NC Vertical triangular NC Horizontal triangular NC Diagonal triangular NC

Transmissions Distribution Fixed number of transmissions Reference table creation Considering all the possible distributions Checking the possible outcomes Calculating the layers that can be decoded Searching in the reference table to find the best transmission distribution

Evaluations- Setting Comparison with Percy method Bus video trace Is performed among the spatio layers Bus video trace 352×288 pixels, 30 frames 4 temporal layer 3 spatio layers Layer 1: 176×144 Layer 2: 320×240 Layer 3: 352×288

Evaluations- Setting Original video Base spatio layer

Evaluations

Evaluations

Evaluations

Conclusions Challenges in multicasting Dependency in multi-layer videos Unequal error protection Two-dimensional triangular network coding Trace-driven evaluation

Thank you