The explosive growth of content-on-the-move, such as video streaming to mobile devices, has propelled research on multimedia broadcast and multicast schemes. Multirate 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 multirate transmission. Furthermore, we establish that the choice of both the network coding technique and the resource-allocation method play a critical role on the network footprint, as well as the quality of each received video layer.
We address the problem of prioritized video streaming over lossy overlay networks. We propose to exploit network path diversity via a novel randomized network coding (RNC) approach that provides unequal error protection (UEP) to the packets conveying the video content. We design a distributed receiver-driven streaming solution, where a client requests packets from the different priority classes from its neighbors in the overlay. Based on the received requests, a node in turn forwards combinations of the selected packets to the requesting peers. Choosing a network coding strategy at every node can be cast as an optimization problem that determines the rate allocation between the different packet classes such that the average distortion at the requesting peer is minimized. As the optimization problem has log-concavity properties, it can be solved with low complexity by an iterative algorithm. Our simulation results demonstrate that the proposed scheme respects the relative priorities of the different packet classes and achieves a graceful quality adaptation to network resource constraints. Therefore, our scheme substantially outperforms reference schemes such as baseline network coding techniques as well as solutions that employ rateless codes with built-in UEP properties. The performance evaluation provides additional evidence of the substantial robustness of the proposed scheme in a variety of transmission scenarios. We formulate the problem of network-coding (NC)-based scheduling for media transmission to multiple users over a wireless-local-area-network-like or WiMAX-like network as a Markov decision process (MDP). NC is used to minimize the packet losses that resulted from unreliable wireless channel conditions, whereas the MDP is employed to find the optimal policy for transmissions of unequally important media packets. Based on this, a dynamic programming technique is used to give an optimal transmission policy. However, this dynamic programming technique quickly leads to computational intractability, even for scenarios with a moderate number of receivers. To address this problem, we further propose a simulation-based dynamic programming algorithm that has a much lower run time yet empirically converges quickly to the optimal solution. In this paper, we study video streaming over wireless networks with network coding capabilities. We build upon recent work, which demonstrated that network coding can increase throughput over a broadcast medium, by mixing packets from different flows into a single packet, thus increasing the information content per transmission. Our key insight is that, when the transmitted flows are video streams, network codes should be selected so as to maximize not only the network throughput but also the video quality. We propose video-aware opportunistic network coding schemes that take into account both the decodability of network codes by several receivers and the importance and deadlines of video packets. Simulation results show that our schemes significantly improve both video quality and throughput. This work is a first step towards content-aware network coding. Recent years have witnessed an explosive growth in multimedia streaming applications over the Internet. Notably, Content Delivery Networks (CDN) and Peer-to-Peer (P2P) networks have emerged as two effective paradigms for delivering multimedia contents over the Internet. One salient feature shared between these two networks is the inherent support for path diversity streaming where a receiver receives multiple streams simultaneously on different network paths as a result of having multiple senders. In this paper, we propose a network coding framework for efficient video streaming in CDNs and P2P networks in which, multiple servers peers are employed to simultaneously stream a video to a single receiver. We show that network coding techniques can (a) eliminate the need for tight synchronization between the senders, (b) be integrated easily with TCP, and (c) reduce server's storage in CDN settings. Importantly, we propose the Hierarchical Network Coding (HNC) technique to be used with scalable video bit stream to combat bandwidth fluctuation on the Internet. Simulations demonstrate that under certain scenarios, our proposed network coding techniques can result in bandwidth saving up to 60 over the traditional schemes.