Network-embedded FEC for optimum throughput of multicast packet video

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Abstract

Forward error correction (FEC) schemes have been proposed and used successfully for multicasting realtime video content to groups of users. Under traditional IP multicast, application-level FEC can only be implemented on an end-to-end basis between the sender and the clients. Emerging overlay and peer-to-peer (p2p) networks open the door for new paradigms of network FEC. The deployment of FEC within these emerging networks has received very little attention (if any). In this paper, we analyze and optimize the impact of network-embedded FEC (NEF) in overlay and p2p multimedia multicast networks. Under NEF, we place FEC codecs in selected intermediate nodes of a multicast tree. The NEF codecs detect and recover lost packets within FEC blocks at earlier stages before these blocks arrive at deeper intermediate nodes or at the final leaf nodes. This approach significantly reduces the probability of receiving undecodable FEC blocks. In essence, the proposed NEF codecs work as signal regenerators in a communication system and can reconstruct most of the lost data packets without requiring retransmission. We develop an optimization algorithm for the placement of NEF codecs within random multicast trees. Based on extensive H.264 video simulations, we show that this approach provides significant improvements in video quality, both visually and in terms of PSNR values.

Introduction

A variety of forward error correction (FEC) frameworks have been proposed and employed for packet loss recovery over the Internet, and especially for multicast applications. Traditional multicast video applications employ FEC on an end-to-end basis between the sender and the clients. However, the reliability and efficiency of end-to-end FEC-based packet video could suffer significantly over large video distribution networks. In this paper, we explore a new alternative for improving the reliability and efficiency (in terms of throughput) of packet video applications by optimum placement of few FEC codecs within large packet-video distribution networks. We develop an optimization algorithm for the placement of FEC codecs within selected nodes of random packet-video networks. We show that this approach provides significant improvements in video quality, both visually and in terms of PSNR values. These significant improvements are achieved while (a) maintaining the desired source-video coding rate, and (b) avoiding any source-video rate shaping or complex transcoding within the network. Hence, our proposed approach is motivated, in part, by the following:

  • First, for many practical realtime video applications, the sender needs to transmit and adhere to a minimum source-video rate. This, for example, could represent the bitrate of the base layer of scalable video, or the rate of a minimum-acceptable quality non-scalable video stream.

  • Second, for many applications, including ones with a large number of receivers, performing complex rate-shaping or transcoding operations may not be desirable or even feasible.

  • Third, emerging and new network paradigms (e.g., [1], [2], [3], [13], [14], [15]), such as overlay and peer-to-peer (p2p) systems, can facilitate the proposed framework for placing FEC codecs within realtime video distribution networks.

It is well known that the overall video quality is directly related to the effective video packet throughput that can be achieved with a given FEC channel-coding rate. However, for a given FEC coding rate (e.g., based on the popular Reed–Solomon FEC method), the packet loss ratio experienced by an end-to-end FEC-based video application could become very high when the number of nodes in the distribution tree increases. This naturally leads to a reduction in video packet throughput. One alternative for improving the reliability of end-to-end FEC solution is to lower the FEC coding rate (i.e., use more redundant packets and less video packets within an FEC block). However, this approach could lead to a significant reduction in the effective source-video rate.1 Furthermore, and as highlighted above, the video application may need to adhere to a minimum source rate. This constraint could be expressed in terms of a rate value k/n, i.e., the sender needs to maintain a transmission rate of k video packets over an n-packet transmission periods. Consequently, in the context of an FEC channel coding, a minimum of k message (video) packets must be included in an n-packet FEC block.

In this work, under a given FEC (n,k) block constraint (i.e., a k/n coding rate constraint), we seek to achieve optimum video-packet throughput by the placement of FEC codecs within selected (optimum) locations (nodes) of the video distribution network. In particular, we analyze and optimize the impact of network-embedded FEC (NEF) within realtime packet video networks. We develop a recursively optimum scheme for the placement of a small number of NEF codecs within any randomly generated multicast video network of known (yet random) link loss rates. In essence, the proposed NEF codecs work as signal regenerators in a communication system, and hence, they can reconstruct the vast majority (and sometimes all) of the lost data packets without requiring retransmission and complex rate shaping and/or transcoding operations. Our theoretical analysis and simulation results show that a relatively small number of NEF codecs placed in (sub-)optimally selected intermediate nodes of a network can improve the throughput and overall reliability dramatically. This leads to the dramatic improvements in the overall video quality observed at the receiving nodes. Fig. 1 shows an example of the proposed NEF framework. It is worth noting that in the proposed NEF framework, the number of added NEF codecs is inherently minimized. This could be important for applications that wish to minimize overall complexity and delay. For example, a particular service may tolerate a certain (maximum) number of NEF codecs between the sender and any receiver. This number can then be used by our NEF (sub-)optimization algorithm to place the desired FEC codecs.

As mentioned above, we envision the deployment of the proposed NEF framework in emerging networks such as overlay and p2p multimedia multicast systems (e.g., [1], [2], [3], [13], [14], [15]). Overlay and p2p networks are becoming increasingly popular for the distribution of shared content over the Internet. Most of the studies conducted for these networks have focused on multicast tree building. Further, these studies assume that reliable transport and congestion control are performed by the underlying end-to-end transport protocol such as TCP. However, TCP favors reliable rather than on-time delivery. Under TCP, the source decreases the sending rate dramatically once congestion is detected, and this makes TCP not appropriate for realtime applications.2 More importantly, the deployment of FEC within emerging networks for realtime multimedia applications has received very little attention (if any).

Under the two types of networks considered here, “overlay” and p2p [1], [2], [3], [13], [14], [15], multicast functions such as membership management and data replication are promoted to the application layer. Here, to distinguish it from a p2p network, an overlay network is equivalent to a proxy-based network3 [3]. In a p2p multicast network, each node in the multicast tree can also be a multicast client (receiver). In a (proxy-based) overlay network, only the leaf nodes are clients. Within both networks, and at each intermediate node, data packets reach the application layer, and then get replicated and forwarded. Hence, in both cases (proxy-based or p2p), packet-loss recovery as an application level service can be placed in the intermediate nodes of the network.

The remainder of the paper is organized as follows. Section 2 presents an analytical model for rate-constrained video throughput using NEF within a multicast packet-video network. Section 3 describes and analyzes a recursive optimization NEF codec placement algorithm. Simulation results for reliability/throughput and for video quality measures are presented in 4 Throughput analysis and simulation results, 5 Video simulations, respectively. Finally, we summarize the key conclusions of this work in Section 6.

Section snippets

Analysis of rate-constrained throughput using network-embedded FEC

Analyzing the impact of FEC on packet losses has been an active research problem that was addressed by previous efforts. In particular, previous studies analyzed the packet-loss model for FEC-enhanced multicast trees (e.g., [10], [11]). These studies are based on the IP multicast model, in which intermediate nodes do not participate in FEC. Here, we study the packet-loss model of a multicast tree when FEC codecs are placed in the intermediate nodes of a tree. In our subsequent analysis and for

Optimum placement of network embedded FEC under a rate constraint

In this section, we develop a mechanism for placing NEF codecs within a given network topology. In a large topology, identifying the optimum locations for the NEF codecs is not a trivial task. One objective is to place codecs in the intermediate nodes of a topology to maximize the average throughput. Assuming that the loss rate for each link in the topology and the number of codecs to be placed are known beforehand,5

Throughput analysis and simulation results

The throughput performance analysis presented above was applied to several random tree topologies. We use the popular Georgia Tech gt-itm [17] network topology generator to produce a set of 10 100-node transit-stub graphs. (Analysis and simulations with trees of larger sizes were also conducted. Here, we focus on the 100-node tree cases for brevity.) For each graph, we use Dijkstra's shortest path first (SPF) algorithm to produce a tree rooted at a randomly selected node. We used the greedy

Video simulations

Discussions in previous sections have concentrated on exhibiting the packet throughput improvements that can be achieved using NEF codecs. At this stage, it is necessary to clearly establish the advantage of using NEF in terms of the quality of video service available at the receivers. We use the emerging H.264/JVT [6] video standard for all the video simulations in this section. All the test sequences considered in this section have a “cif” frame size and are encoded at a frequency of 30

Conclusion

In this paper, we explored a new approach for improving the reliability and throughput of packet video by optimum placement of FEC codecs within large packet video distribution networks. We developed an optimization algorithm for the placement of FEC codecs within selected nodes of random packet-video networks. We also demonstrated that this approach provides significant improvements in video quality, both visually and in terms of PSNR values. Our proposed approach has been motivated by (a) the

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Cited by (0)

Part of this work has been presented as: Mingquan Wu, Shirish Karande, and Hayder Radha, “Network-Embedded Channel Coding for Optimum Throughput of Multicast Packet Video”, International Packet Video Workshop (PV), December 2004. Hayder Radha and Mingquan Wu, “Overlay and Peer-to-Peer Multimedia Multicast with Network-Embedded FEC”, IEEE International Conference on Image Processing (ICIP), October 2004.

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