Network Coding Over SATCOM: Lessons Learned

Satellite networks provide unique challenges that can restrict users' quality of service. For example, high packet erasure rates and large latencies can cause significant disruptions to applications such as video streaming or voice-over-IP. Network coding is one promising technique that has been shown to help improve performance, especially in these environments. However, implementing any form of network code can be challenging. This paper will use an example of a generation-based network code and a sliding-window network code to help highlight the benefits and drawbacks of using one over the other. In-order packet delivery delay, as well as network efficiency, will be used as metrics to help differentiate between the two approaches. Furthermore, lessoned learned during the course of our research will be provided in an attempt to help the reader understand when and where network coding provides its benefits.Comment: Accepted to WiSATS 201

Machine Learning for Multimedia Communications

Machine learning is revolutionizing the way multimedia information is processed and transmitted to users. After intensive and powerful training, some impressive efficiency/accuracy improvements have been made all over the transmission pipeline. For example, the high model capacity of the learning-based architectures enables us to accurately model the image and video behavior such that tremendous compression gains can be achieved. Similarly, error concealment, streaming strategy or even user perception modeling have widely benefited from the recent learningoriented developments. However, learning-based algorithms often imply drastic changes to the way data are represented or consumed, meaning that the overall pipeline can be affected even though a subpart of it is optimized. In this paper, we review the recent major advances that have been proposed all across the transmission chain, and we discuss their potential impact and the research challenges that they raise

Information-Centric Multilayer Networking: Improving Performance Through an ICN/WDM Architecture

Information-centric networking (ICN) facilitates content identification in networks and offers parametric representation of content semantics. This paper proposes an ICN/WDM network architecture that uses these features to offer superior network utilization, in terms of performance and power consumption. The architecture introduces an ICN publish/subscribe communication approach to the wavelength layer, whereby content is aggregated according to its popularity rank into wavelength-size groups that can be published and subscribed to by multiple nodes. Consequently, routing and wavelength assignment (RWA) algorithms benefit from anycast to identify multiple sources of aggregate content and allow optimization of the source selection of light paths. A power-aware algorithm, maximum degree of connectivity, has been developed with the objective of exploiting this flexibility to address the tradeoff between power consumption and network performance. The algorithm is also applicable to IP architectures, albeit with less flexibility. Evaluation results indicate the superiority of the proposed ICN architecture, even when utilizing conventional routing methods, compared with its IP counterpart. The results further highlight the performance improvement achieved by the proposed algorithm, compared with the conventional RWA methods, such as shortest-path first fit

Adaptive Video Streaming with Network Coding enabled Named Data Networking

The fast and huge increase of Internet traffic motivates the development of new communication methods that can deal with the growing volume of data traffic. To this aim, named data networking (NDN) has been proposed as a future Internet architecture that enables ubiquitous in-network caching and naturally supports multipath data delivery. Particular attention has been given to using dynamic adaptive streaming over HTTP to enable video streaming in NDN as in both schemes data transmission is triggered and controlled by the clients. However, state-of-the-art works do not consider the multipath capabilities of NDN and the potential improvements that multipath communication brings, such as increased throughput and reliability, which are fundamental for video streaming systems. In this paper, we present a novel architecture for dynamic adaptive streaming over network coding enabled NDN. In comparison to previous works proposing dynamic adaptive streaming over NDN, our architecture exploits network coding to efficiently use the multiple paths connecting the clients to the sources. Moreover, our architecture enables efficient multisource video streaming and improves resiliency to Data packet losses. The experimental evaluation shows that our architecture leads to reduced data traffic load on the sources, increased cache-hit rate at the in-network caches and faster adaptation of the requested video quality by the clients. The performance gains are verified through simulations in a Netflix-like scenario

Content-Aware Delivery of Scalable Video in Network Coding Enabled Named Data Networks

We propose a novel network coding (NC) enabled named data networking (NDN) architecture for scalable video delivery. Our architecture utilizes network coding in order to address the problem that arises in the original NDN architecture, where optimal use of the bandwidth and caching resources necessitates the coordination of the Interest forwarding decisions. To optimize the performance of the proposed network coding based NDN architecture and render it appropriate for transmission of scalable video, we devise a novel rate allocation algorithm that decides on the optimal rates of Interests sent by clients and intermediate nodes. The flow of Data packets achieved by this algorithm maximizes the average quality of the video delivered to the client population. To support the handling of Interest and Data packets when intermediate nodes perform network coding, we introduce the use of Bloom filters, which store efficiently additional information about the Interest and Data packets, and modify accordingly the standard NDN architecture. We also devise an optimized Interest forwarding strategy that implements the target rate allocation. The proposed architecture is evaluated for transmission of scalable video over PlanetLab topologies. The evaluation shows that the proposed scheme exploits optimally the available network resources

NetCodCCN: A network coding approach for content-centric networks

Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of distribution trees should be determined in order to optimally use all the available interfaces. This is not a trivial task, as it is a computationally intense procedure that should be done centrally. The need for central coordination can be removed by employing network coding, which also offers improved resiliency to errors and large throughput gains. In this paper, we propose NetCodCCN, a protocol for integrating network coding in CCN. In comparison to previous works proposing to enable network coding in CCN, NetCodCCN permits Interest aggregation and Interest pipelining, which reduce the data retrieval times. The experimental evaluation shows that the proposed protocol leads to significant improvements in terms of content retrieval delay compared to the original CCN. Our results demonstrate that the use of network coding adds robustness to losses and permits to exploit more efficiently the available network resources. The performance gains are verified for content retrieval in various network scenarios

Network coding: from theory to media streaming

Network coding has recently emerged as an alternative to traditional routing algorithms in communication systems. In network coding, the network nodes can combine the packets they receive before forwarding them to the neighbouring nodes. Intensive research efforts have demonstrated that such a processing in the network nodes can provide advantages in terms of throughput or robustness. These potentials, combined with the advent of ad hoc and wireless delivery architectures have triggered the interest of research community about the application of the network coding principles to streaming applications. This paper describes the potentials of network coding in emerging delivery architectures such as overlay or peer-to-peer networks. It overviews the principles of practical network coding algorithms and outlines the challenges posed by multimedia streaming applications. Finally, it provides a survey of the recent work on the application of network coding to media streaming applications, both in wireless or wired communication scenarios. Promising results have been demonstrated where network coding is able to bring benefits in media streaming applications. However, delay and complexity constraints are often posed as the main challenging issues that still prevent the wide-scale deployment of network coding algorithms in multimedia communication

Collaborative video streaming with Raptor network coding

We investigate the problem of collaborative video streaming with Raptor network coding over overlay networks. We exploit path and source diversity, as well as basic processing capabilities of network nodes to increase the overall throughput and improve the video quality at the clients. We consider an architecture where several streaming servers simultaneously deliver video information to a set of clients. The servers apply Raptor coding on the video packets for error resiliency, and the forwarding peer nodes further combine the Raptor coded video packets in order to increase the packet diversity in the network. We find the optimal source and channel rate allocation in such a collaborative streaming system. The resulting scheme efficiently exploits the available network resources for improved video quality. The experimental evaluation demonstrates that it typically outperforms Raptor video streaming systems that do not use network coding

Network coding node placement for delay minimization in streaming overlays

Network coding has been proposed recently as an efficient method to increase network throughput by allowing network nodes to combine packets instead of simply forwarding them. However, packet combinations in the network may increase delay, complexity and even generate overly redundant information when they are not designed properly. Typically, the best performance is not achieved when all the nodes perform network coding. In this paper, we address the problem of efficiently placing network coding nodes in overlay networks, so that the rate of innovating packets is kept high, and the delay for packet delivery is kept small. We first estimate the expected number of duplicated packets in each network node. These estimations permit to select the nodes that should implement network coding, so that the innovating rate increases. Two algorithms are then proposed for the cases where a central node is aware of the full network statistics and where each node knows the local statistics from its neighbor, respectively. The simulation results show that in the centralized scenario the maximum profit from network coding comes by adding only a few network coding nodes. A similar result is obtained with the algorithm based on local statistics, which moreover performs very close to the centralized solution. These results show that the proper selection of the network coding nodes is crucial for minimizing the transmission delay in streaming overlays

Multiview video representations for quality-scalable navigation

Interactive multiview video (IMV) applications offer to users the freedom of selecting their preferred viewpoint. Usually, in these systems texture and depth maps of captured views are available at the user side, as they permit the rendering of intermediate virtual views. However, the virtual views' quality depends on the distance to the available views used as references and on their quality, which is generally constrained by the heterogeneous capabilities of the users. In this context, this work proposes an IMV scalable system, where views are optimally organized in layers, each one offering an incremental improvement in the interactive navigation quality. We propose a distortion model for the rendered virtual views and an algorithm that selects the optimal views' subset per layer. Simulation results show the efficiency of the proposed distortion model, and that the careful choice of reference cameras permits to have a graceful quality degradation for clients with limited capabilities