As handheld devices are getting increasingly popular for delivering multimedia content, this paper presents our ongoing project in developing open source peer-to-peer video streaming solution over the Symbian platform. Specifically, we describe the system architecture and key components, and discuss the challenges and limitations.

Peer-to-peer (P2P) based live video streaming system has emerged as a promising solution for the Internet video streaming applications, partly evident from commercial deployment of several large-scale P2P streaming systems. The key is to leverage the resources available at end users, which offers great potential to scale in the Internet. Flash crowd poses a unique challenge for live streaming systems, in which there could be potentially hundred of thousands of users joining the system during the initial few minutes of a live program. This adds considerable difficulty in particular for a P2P based system in quickly ramping to a scale that can provide reasonable streaming services for newly incoming peers. In this paper, we examine the system dynamics under flash crowd based on measurements obtained from the Coolstreaming system. We are particularly concerned with the impact and user behaviors during flash crowd. The results reveal a number of interesting observations: (1) the system can scale up to a limit during the flash crowd; (2) there is a strong correlation between the number of short sessions and joining rate due to the resource competition among newly joined peers; (3) the user behavior during flash crowd can be best captured by the number of retries and the impatience time.

The peer-to-peer (P2P) based video streaming has emerged as a promising solution for Internet video distribution. Leveraging the resource available at end users, this approach poses great potential to scale in the Internet. We have now seen the commercial P2P streaming systems that are orders of magnitude larger than the earlier academic systems. We believe understanding its basic principles and limitations are important in the design of future systems. The Coolstreaming, first released in summer 2004, arguably represented the first successful large-scale P2P live streaming system. Since then, the system has been significantly modified and commercially launched. This paper takes an inside look at the new Coolstreaming system by exposing its design options and rationale behind them, and examines their implications on streaming performance. Specifically, by leveraging a large set of traces obtained from recent live event broadcast and extensive simulations, we study the workload characteristics, system dynamics, and impact from a variety of system parameters. We demonstrate that there is a highly skewed resource distribution in such systems and the performance is mostly affected by the system dynamics. In addition, we show that there are inherent correlations and fundamental trade-off among different system parameters, which can be further explored to enhance the system performance.

In recent years, there has been significant interest in adopting the peer-to-peer (P2P) technology for Internet live video streaming. There are primarily two reasons behind this development: the elimination of infrastructure support and the self-scaling property of P2P systems. The success of our system Coolstreaming represented one of the earliest large-scale P2P video streaming experiments. Since then, there have been several large-scale commercial deployments. With desirable content, these systems have the potential to scale orders of magnitude beyond the existing academic P2P prototypes. However, to transform this potential into reality, we need to understand the key design trade-offs and principles, as well as the design limitations of these systems. There are two main design decisions in a P2P streaming system: (i) How to form an overlay, and (ii) How to deliver the content. Coolstreaming adopts a gossiping protocol for overlay construction, and a swarm-based protocol for content delivery. While these protocols provide excellent flexibility and effectiveness in dealing with system dynamics and random failure, their impact on the performance and the system scalability remain less known. This paper takes an inside look at a commercial system based on the Coolstreaming, called Coolstreaming+. We explore its design choices and the impact of these choices on streaming performance. Specifically, by using internal traces generated by recent live broadcast events, we study the workload, performance, and dynamics of the system. Based on these traces, we show that (1) the churn is the most critical factor that affects the overall performance of the system, and (2) there is a highly skew resource distribution in P2P streaming systems, which has significant impact on resource allocation. We further discuss the impact of these observations on the system properties, and present solutions to deal with various design challenges. In particular, we suggest solutions to deal with the excessive start-up time and high failure rates during flash crowd, which are two of the main challenges any streaming system needs to address.

Peer-to-peer (P2P) technology has found much success in applications like file distributions and VoIP yet, its adoption in live video streaming remains as an elusive goal. Our recent success in Coolstreaming system brings promises in this direction; however, it also reveals that there exist many practical engineering problems in real live streaming systems over the Internet. Our focus in this paper is on a nonoptimal real working system, in which we illustrate a set of existing practical problems and how they could be handled. We believe this is essential in providing the basic understanding of P2P streaming systems. This paper uses a set of real traces and attempts to develop some theoretical basis to demonstrate that a random peer partnership selection with a hybrid pull-push scheme has the potentially to scale. Specifically, first, we describe the fundamental system design tradeoffs and key changes in the design of a Coolstreaming system including substreaming, buffer management, scheduling and the adopt of a hybrid pull-push mechanism over the original pull-based content delivery approach; second, we examine the overlay topology and its convergence; third, using a combination of real traces and analysis, we quantitatively provide the insights on how the buffering technique resolves the problems associated with dynamics and heterogeneity; fourth, we show how substream and path diversity can help to alleviate the impact from congestion and churns; fifth, we discuss the system scalability and limitations.