Michael Eberhard

Knapsack problem-based piece-picking algorithms for layered content in peer-to-peer networks

The distribution of layered content over peer-to-peer networks becomes more important today as the users are consuming the content on terminals with various display capabilities and different network connections. For single-layer content distribution, the piece-picking algorithm only needs to ensure that content pieces are downloaded in time for display. When layered content is distributed over a peer-to-peer network, the piece-picking algorithm needs to be modified to ensure that the best possible quality is displayed while all desired pieces still have to be received before their deadline expires. In this paper, the piece-picking problem for layered content is analyzed and a number of piece-picking algorithms for layered content based on the solutions for the knapsack problem are presented. Furthermore, an evaluation of these algorithms is performed and possible applications are discussed.

An Architecture for Distributing Scalable Content over Peer-to-Peer Networks

Peer-to-Peer systems are nowadays a very popular solution for multimedia distribution, as they provide significant cost benefits compared with traditional server-client distribution. Additionally, the distribution of scalable content enables the consumption of the content in a quality suited for the available bandwidth and the capabilities of the end-user devices. Thus, the distribution of scalable content over P2P networks is a very actual research topic. This paper presents an architecture for the distribution of scalable content in a fully distributed Peer-to-Peer network. The architectural description includes how the scalable layers of the content are mapped to the pieces distributed in the Peer-to-Peer system and detailed descriptions of the producer- and consumer-site architecture of the system. The presented system is to our knowledge the first open-source Peer-to-Peer network with full Scalable Video Coding support.

Piece Selection Algorithm for Layered Video Streaming in P2P Networks

Abstract This paper introduces the piece selection problem that arises when streaming layered video content over peer-to-peer networks. The piece selection algorithm decides periodically which pieces to request from other peers (network nodes) for download. The main goal of the piece selection algorithm is to provide the best possible quality for the available bandwidth. Our recommended solution approaches are related to the typical problems and solutions in the knapsack problem.

Performance Analysis of Scalable Video Adaptation: Generic versus Specific Approach

This paper provides a performance analysis of adaptation approaches designed for scalable media resources. In particular, we investigate the streaming of media resources compliant to the scalable video coding (SVC) extensions of advanced video coding (AVC) within heterogeneous environments, i.e., terminals and networks with different capabilities. Therefore, we have developed a test-bed in order to analyze two different approaches for the adaptation of scalable media resources, namely a generic approach that is applicable independently of the actual scalable coding format used and a specific approach especially built for SVC. The results show that if adaptation is required the generic approach clearly outperforms the approach specifically built for SVC.

Deftpack: A Robust Piece-Picking Algorithm for Scalable Video Coding in P2P Systems

The volume of Internet video is growing, and is expected to exceed 57 percent of global consumer Internet traffic by 2014. Peer-to-Peer technology can help delivering this massive volume of traffic in a cost-efficient, scalable, and reliable manner. However, single bit rate streaming is not sufficient given todays device and network connection diversity. A possible solution to this problem is provided by layered coding techniques, such as Scalable Video Coding, which allow addressing this diversity by providing content in various qualities within a single bit stream. In this paper we propose a new self-adapting piece-picking algorithm for downloading layered video streams, called Deft pack. Our algorithm significantly reduces the number of stalls, minimises the frequency of quality changes during playback, and maximizes the effective usage of the available bandwidth. Deft pack is the first algorithm that is specifically crafted to take all these three quality dimensions into account simultaneously, thus increasing the overall quality of experience. Additionally, Deft pack can be integrated into Bit torrent-based P2P systems and so has the chance of large-scale deployment. Our results from realistic swarm simulations show that Deft pack significantly outperforms previously proposed algorithms for retrieving layered content when all three quality dimensions are taken into account.

Piece selection algorithms for layered video streaming in P2P networks

This paper introduces the piece selection problem that arises when streaming layered video content over peer-to-peer networks. The piece selection algorithm decides periodically which pieces to request from other peers (network nodes) for download. The main goal of the piece selection algorithm is to provide the best possible quality for the available bandwidth. Our recommended solution approaches are related to the knapsack problem. In this paper, a number of layered piece picking algorithms are presented and they are compared to each other. In a competitive analysis, the presented online algorithms are compared to an optimal offline algorithm.

An interoperable multimedia delivery framework for scalable video coding based on MPEG-21 Digital Item Adaptation

In this paper we present an interoperable multimedia delivery framework for scalable video coding based on MPEG-21 digital item adaptation (DIA). In can be used to transmit scalable video contents within heterogeneous usage environments where the properties of the usage environment (e.g., terminal/network capabilities) may change dynamically during the streaming session. The usage environment is signaled by interoperable description formats provided by the DIA standard. Additionally, the adaptation itself is done by exploiting the standardpsilas generic adaptation approach, i.e., independent of the actual coding format. Thus, the overall framework is also applicable for other scalable coding formats.

An evaluation of piece-picking algorithms for layered content in Bittorrent-based peer-to-peer systems

In this paper the performance of layered piece-picking algorithms for Bittorrent-based peer-to-peer systems is evaluated and compared to traditional single layer solutions. In a Bittorrent-based peer-to-peer system, the piece-picking algorithm needs to ensure that the pieces of an audiovisual content are received in time to ensure smooth playback of the content. For layered content provided in multiple qualities, the task of the algorithm becomes more complex, as it has to consider the layer of the pieces to be fetched in addition to the deadline. Thus, the goal of the layered piece-picking algorithm is to ensure that the best possible quality under the given network conditions is received while the playback is not disturbed. To illustrate the advantages of such a layered piece-picking algorithm, its performance is evaluated and compared to a single layer piece-picking algorithm. The results show that layered piece-picking algorithms can significantly improve the quality in terms of peak signal-to-noise ratio.

An interoperable delivery framework for scalable media resources

In this article an interoperable framework for the delivery of scalable media resources (e.g., in the standardized scalable video coding format) is presented. The framework provides support for video on demand as well as multicast streaming, and performs efficient, generic, and interoperable adaptation of streamed content based on MPEG- 21 Digital Item Adaptation. The server as well as the clients of the streaming framework implement the MPEG Extensible Middleware and utilize the MPEG Query Format for querying the available media resources. The framework has been fully integrated into the VLC media player. The architecture for both VoD and multicast is presented in detail. Finally, a comparison in terms of performance of the generic MPEG-21 metadata-based adaptation approach to an SVC-specific adaptation approach is provided.

Comparison of piece-picking algorithms for layered video content in peer-to-peer networks

The distribution of video content over P2P systems has become a popular and cost-effective option in recent years due to the increasing online availability of content. Additionally, the diversity of end-user terminals used for consuming content demands the provisioning of content in different qualities. Both problems are addressed by distributing layered video content over P2P networks. A piece-picking algorithm for layered video content needs to ensure that the pieces are received in time as well as that the best possible quality that can be processed by the end-user terminal and downloaded under the given network conditions is provided. In this paper, we describe our algorithm for piece-picking of layered video content in Bittorrent-based P2P systems and compare it to other existing piece-picking algorithms. The evaluation presented in this paper shows that our algorithm can very well compete with previously published algorithms.