Application layer error-correction coding for rate-distortion optimized streaming to wireless clients

This paper addresses the problem of streaming packetized media over a lossy packet network to a wireless client, in a rate-distortion optimized way. We introduce an incremental redundancy error-correction scheme that combats the effects of both packet loss and bit errors in an end-to-end fashion, without support from the underlying network or from an intermediate base station. The scheme is employed within an optimization framework that enables the sender to compute which packets it should send, out of all the packets it could send at a given transmission opportunity, in order to meet an average transmission-rate constraint while minimizing the average end-to-end distortion. Experimental results show that our system is robust and maintains quality of service over a wide range of channel conditions. Up to 8 dB performance gains are registered over systems that are not rate-distortion optimized, at bit-error rates as large as 10/sup -2/.     

Enabling adaptive video streaming in P2P systems [Peer-to-Peer Multimedia Streaming]

Peer-to-peer (P2P) systems are becoming increasingly popular due to their ability to deliver large amounts of data at a reduced deployment cost. In addition to fostering the development of novel media applications, P2P systems also represent an interesting alternative paradigm for media streaming applications that can benefit from the inherent self organization and resource scalability available in such environments. This article presents an overview of application and network layer mechanisms that enable successful streaming frameworks in peer-to-peer systems. We describe media delivery architectures that can be deployed over P2P networks to address the specific requirements of streaming applications. In particular, we show how video-streaming applications can benefit from the diversity offered by P2P systems and implement distributed-streaming and scheduling solutions with multi-path packet transmission.     

The Virtue of Patience in Low-Complexity Scheduling of Packetized Media With Feedback

We consider streaming pre-encoded and packetized media over best-effort networks in the presence of acknowledgment feedbacks. We first review a rate-distortion (RD) optimization framework that can be employed in such scenarios. As part of the framework, a scheduling algorithm selects the data to send over the network at any given time, so as to minimize the end-to-end distortion, given an estimate of channel resources and a history of previous transmissions and received acknowledgements. In practice, a greedy scheduling strategy is often considered to limit the solution search space, and reduce the computational complexity associated to the RD optimization framework. Our work observes that popular greedy schedulers are strongly penalized by early retransmissions. Therefore, we propose a scheduling algorithm that avoids premature retransmissions, while preserving the low computational complexity aspect of the greedy paradigm. Such a scheduling strategy maintains close to optimal RD performance when adapting to network bandwidth fluctuations. Our experimental results demonstrate that the proposed patient greedy scheduler provides a reduction of up to 50% in transmission rate relative to conventional greedy approaches, and that it brings up to 2 dB of quality improvement in scheduling classical MPEG-based packet video streams     

Rate-distortion optimized distributed packet scheduling of multiple video streams over shared communication resources

We consider the problem of distributed packet selection and scheduling for multiple video streams sharing a communication channel. An optimization framework is proposed, which enables the multiple senders to coordinate their packet transmission schedules, such that the average quality over all video clients is maximized. The framework relies on rate-distortion information that is used to characterize a video packet. This information consists of two quantities: the size of the packet in bits, and its importance for the reconstruction quality of the corresponding stream. A distributed streaming strategy then allows for trading off rate and distortion, not only within a single video stream, but also across different streams. Each of the senders allocates to its own video packets a share of the available bandwidth on the channel in proportion to their importance. We evaluate the performance of the distributed packet scheduling algorithm for two canonical problems in streaming media, namely adaptation to available bandwidth and adaptation to packet loss through prioritized packet retransmissions. Simulation results demonstrate that, for the difficult case of scheduling nonscalably encoded video streams, our framework is very efficient in terms of video quality, both over all streams jointly and also over the individual videos. Compared to a conventional streaming system that does not consider the relative importance of the video packets, the gains in performance range up to 6 dB for the scenario of bandwidth adaptation, and even up to 10 dB for the scenario of random packet loss adaptation.     

Distributed Collaboration for Enhanced Sender-Driven Video Streaming

We propose a sender-driven system for adaptive streaming from multiple servers to a single receiver over separate network paths. The servers employ information in receiver feedbacks to estimate the available bandwidth on the paths and then compute appropriate transmission schedules for streaming media packets to the receiver based on the bandwidth estimates. An optimization framework is proposed that enables the senders to compute their transmission schedules in a distributed way, and yet to dynamically coordinate them over time such that the resulting video quality at the receiver is maximized. To reduce the computational complexity of the optimization framework an alternative technique based on packet classification is proposed. The substantial reduction in online complexity due to the resulting packet partitioning makes the technique suitable for practical implementations of adaptive and efficient distributed streaming systems. Simulations with Internet network traces demonstrate that the proposed solution adapts effectively to bandwidth variations and packet loss. They show that the proposed streaming framework provides superior performance over a conventional distortion-agnostic scheme that performs proportional packet scheduling on the network paths according to their respective bandwidth values.     

RaDiO Edge: Rate-Distortion Optimized Proxy-Driven Streaming From the Network Edge

This paper addresses the problem of streaming packetized media over a lossy packet network through an intermediate proxy server to a client, in a rate-distortion optimized way. The proxy, located at the junction of the backbone network and the last hop to the client, coordinates the communication between the media server and the client using hybrid receiver/sender-driven streaming in a rate-distortion optimization framework. The framework enables the proxy to determine at every instant which packets, if any, it should either request from the media server or (re)transmit directly to the client, in order to meet constraints on the average transmission rates on the backbone and the last hop while minimizing the average end-to-end distortion. Performance gains are observed over rate-distortion optimized sender-driven systems for streaming packetized video content. The improvement in performance depends on the quality of the network path both in the backbone network and along the last hop     

Adaptive systems for improved media streaming experience

Supporting streaming media applications over current packet network infrastructures represents a challenging task in many regards. For one, the lack of quality of service (QoS) guarantees in existing networks such as the Internet means that time-constrained media packets will face dynamic variations in bandwidth, loss rate, and delay as they traverse the network from the sender to the receiver. The variable rate of media traffic represents yet another difficulty when transmission constraints need to be met. Finally, the heterogeneity of client devices and access bandwidth coupled with custom user preferences exacerbate the problem of smooth and quality-optimized media playback even further. In this article we provide an overview of the various techniques for media and streaming strategy adaptation, which can be employed to deal with the difficulties imposed by such dynamic environments. These techniques depend on the characteristics of the media application, in particular on the network streaming infrastructure and the timing constraints imposed on the media packets' delivery. We survey adaptation techniques that act on the encoding of the multimedia information, on the scheduling of the media packets, or that try to combat transmission errors. We also briefly overview some media-friendly networking solutions, which contribute to increased QoS by incorporating some level of intelligence in intermediate network nodes. Finally, we describe a few open challenges in media streaming, emphasizing strategies based on promising cross-layer approaches where adaptation strategies are applied in a coordinated manner, across different layers of the network protocol stack     

Product backlog rating: a case study on measuring test quality in scrum

Agile software development methodologies focus on software projects which are behind schedule or highly likely to have a problematic development phase. In the last decade, Agile methods have transformed from cult techniques to mainstream methodologies. Scrum, an Agile software development method, has been widely adopted due to its adaptive nature. This paper presents a metric that measures the quality of the testing process in a Scrum process. As product quality and process quality correlate, improved test quality can ensure high-quality products. Also, gaining experience from 8 years of successful Scrum implementation at SoftwarePeople, we describe the Scrum process emphasizing the testing process. We propose a metric Product Backlog Rating (PBR) to assess the testing process in Scrum. PBR considers the complexity of the features to be developed in an iteration of Scrum, assesses test ratings and offers a numerical score of the testing process. This metric is able to provide a comprehensive overview of the testing process over the development cycle of a product. We present a case study which shows how the metric is used at SoftwarePeople. The case study explains some features that have been developed in a Sprint in terms of feature complexity and potential test assessment difficulties and shows how PBR is calculated during the Sprint. We propose a test process assessment metric that provides insights into the Scrum testing process. However, the metric needs further evaluation considering associated resources (e.g., quality assurance engineers, the length of the Scrum cycle).     

Multi-path content delivery: Efficiency analysis and optimization algorithms

The paper studies the benefits of multi-path content delivery from a rate-distortion efficiency perspective. We develop an optimization framework for computing transmission schedules for streaming media packets over multiple network paths that maximize the end-to-end video quality, for the given bandwidth resources. We comprehensively address the two prospective scenarios of content delivery with packet path diversity. In the context of sender-driven systems, our framework enables the sender to compute at every transmission instance the mapping of packets to network paths that meets a rate constraint while minimizing the end-to-end distortion. In receiver-driven multi-path streaming, our framework enables the client to dynamically decide which packets, if any, to request for transmission and from which media servers, such that the end-to-end distortion is minimized for a given transmission rate constraint. Via simulation experiments, we carefully examine the performance of the scheduling framework in both multi-path delivery scenarios. We demonstrate that the optimization framework closely approaches the performance of an ideal streaming system working at channel capacity with an infinite play-out delay. We also show that the optimization leads to substantial gains in rate-distortion performance over a conventional content-agnostic scheduler. Through the concept of error-cost performance for streaming a single packet, we provide another useful insight into the operation of the optimization framework and the conventional scheduling system.