Abstract — Most of the real deployed peer-to-peer streaming systems adopt pull-based streaming protocol. In this paper, we demonstrate that, besides simplicity and robustness, with proper parameter settings, when the server bandwidth is above several times of the raw streaming rate, which is reasonable for practical live streaming system, simple pull-based P2P streaming protocol is nearly optimal in terms of peer upload capacity utilization and system throughput even without intelligent scheduling and bandwidth measurement. We also indicate that whether this near optimality can be achieved depends on the parameters in pull-based protocol, server bandwidth and group size. Then we present our mathematical analysis to gain deeper insight in this characteristic of pull-based streaming protocol. On the other hand, the optimality of pull-based protocol comes from a cost-tradeoff between control overhead and delay, that is, the protocol has either large control overhead or large delay. To break the tradeoff, we propose a pull-push hybrid protocol. The basic idea is to consider pull-based protocol as a highly efficient bandwidthaware multicast routing protocol and push down packets along the trees formed by pull-based protocol. Both simulation and real-world experiment show that this protocol is not only even more effective in throughput than pull-based protocol but also has far lower delay and much smaller overhead. And to achieve near optimality in peer capacity utilization without churn, the server bandwidth needed can be further relaxed. Furthermore, the proposed protocol is fully implemented in our deployed GridMedia system and has the record to support over 220,000 users simultaneously online. Index Terms — p2p streaming, pull-based, pull-push hybrid, capacity utilization, throughput, delay I.

Live peer to peer (P2P) media streaming faces many challenges such as peer unreliability and bandwidth heterogeneity. To effectively address these challenges, general “mesh ” based P2P streaming architectures have recently been adopted. Mesh-based systems allow peers to aggregate bandwidth from multiple neighbors, and dynamically adapt to changing network conditions and neighbor failures. However, a drawback of mesh-based overlays is that it is difficult to guarantee network connectivity in a distributed fashion, especially when network locality needs to be optimized. This paper introduces a new P2P streaming framework called DagStream, which (1) organizes peers into a directed acyclic graph (DAG) where each node maintains at least k parents, thus has provable network connectivity (and hence failure resilience), and (2) enables peers to quickly achieve locality awareness in a distributed fashion, thus ensures efficient network resource usage. Our experiment results in both simulation and wide area environment show that with our DagStream protocol, peers can quickly self-organize into a locality aware DAG. Further, by selecting additional parents as needed, peers can achieve good streaming quality commensurate with their downlink bandwidth. 1.

Abstract—The Internet has witnessed a rapid growth in deployment of data-driven overlay network (DON) based streaming applications during recent years. In these applications, each nodes independently selects some other nodes as its neighbors (i.e. overlay construction), and exchanges streaming data with these neighbors (i.e. data scheduling). This scheme improves the robustness of the system. However, most of the work in the literature has been focusing on the construction problem, and very few addressed its scheduling problem which is also very important for the overall performance. In this paper, we analytically study the scheduling problem in DON and model it as a classical min-cost network flow problem. We then propose both the global optimal scheduling scheme and distributed heuristic algorithm to maximize the system throughput. Experimental results indicate that our algorithms outperform other schemes and the throughput gain is up to 80% 1.

Abstract. Recently, much attention has been paid on data-driven (or swarm-like) based live streaming systems due to its rapid growth in deployment over Internet. In such systems, nodes randomly select their neighbors to form an unstructured overlay mesh (gossip-style overlay construction) and then each node requests desired data blocks from its neighbors (block scheduling). To improve the performance, most of existing works focus on the gossip-style overlay construction issue; however few concentrate on optimizing the block scheduling for improving the throughput of a constructed overlay, especially in heterogeneous environment. In this paper, we propose a scheme to optimize the throughput of data-driven streaming systems in heterogeneous overlay network. We first model the block scheduling problem as a classical min-cost flow problem and thereby derive a global optimal solution. Based on this idea, we then propose DONLE- a fully distributed asynchronous scheduling algorithm. Simulation results verify that DONLE is superior to a number of conventional strategies. 1

Abstract — Most existing overlay multicast proposals have assumed that the nodes are cooperative and thus focus on the global topology optimization. However, a unique and important characteristic of overlay nodes is that, as application-layer agents, they can be selfish with their own interests. To achieve better Quality-of-Service (QoS) or to minimize forwarding overhead, an overlay node can behave selfishly in the information collection or in the overlay construction. While the former has recently been investigated, the impact of selfishness in the construction action remains unclear. In this paper, we present the first systematic study on the impact of selfishness in both tree and mesh overlay construction. Our investigation considers multiple QoS measures for streaming applications, including stream latency, resolution, and continuity. Our contribution is twofold: First, we analyze how for selfish overlay nodes to choose a construction-action policy to optimize their individual multi-metric QoS. Second, we demonstrate that the selfishness-aware policy for the construction action is consistent with the QoS optimization for the global multicast session, but not vice versa. The implication is significant: A globally optimal overlay construction itself can be vulnerable to individual selfishness; but, following our directions, we can design an overlay that is both globally optimal and selfish-resistant. I.

IPTV, or Internet-Based TV broadcasting is going to significantly change the way people obtain information, get entertainment, and possibly collaborate with each other. Compared with today’s TV system, IPTV gives the viewers more choice as to what to watch and how to watch, and allows users to broadcast their own programs easily, thus “democratizing ” information broadcasting. To realize the vision of IPTV, however, there are many challenging issues, such as content-based channel discovery and selection, user view customization, and efficient media streaming. This position paper describes a framework for future IPTV systems where millions of viewers can select multiple channels, view them in a customized way, and cooperate with each other in a peer-to-peer fashion for TV program delivery.

Abstract—Although layered streaming in heterogeneous peer-to-peer networks has drawn great interest in recent years, there’s still a lack of systematical studies on its data scheduling issue. In this paper, we propose a new scheduling approach for layered video streaming, called LayerP2P. The key idea and main contributions of LayerP2P come in two-fold: 1) According to the characteristics caused by layered coding, we propose four objectives that should be achieved by data scheduling: high throughput, high layer delivery ratio, low useless packets ratio, and low subscription jitter; 2) We design a 3-stage scheduling mechanism to request absent blocks, where the min-cost flow model, probability decision mechanism and multi-window remedy mechanism are employed in Free Stage, Decision Stage and Remedy Stage, respectively. Each stage has different scheduling objective while collaborates with each other, to achieve the above four objectives. Experimental results indicate that our approach outperforms other schemes in simulation environment. Besides, LayerP2P is implemented in the PDEPS Project in China, which is expected to be the first practical layered streaming system for education in peer-to-peer networks. I.

Recent research in peer-to-peer and grid computing has made it possible to build Inter-net scale services such as content distribution, storage service, name service and pub-lish/subscribe. By utilizing large number of service nodes that collaborate in a decentralized fashion, such services can potentially achieve high scalability, availability, reliability and QoS/performance. Despite such potential, building large distributed services and testing them in a real world, widely distributed environment remains a difficult task. This is be-cause first, a wide area environment is full of various network and node failures. Therefore, services targeting such environment must have built-in mechanisms to deal with such fail-ures. Further, such mechanisms must not rely on centralized control, due to the scale of the services. Second, running services in a wide area environment requires system support for deploying, monitoring and controlling the services. However, current computing infrastruc-tures generally lack powerful tools for managing widely distributed services. As a result, service developers often have to resort to ad hoc methods for service management. In this dissertation we present our research aimed at simplifying the development of large

Layered video streaming in peer-to-peer networks has drawn great interests since not only it can accommodate a large number of users but also it handles heterogeneities of client networks. However, to our knowledge, there’s still a lack of systematical study on the data scheduling (i.e. requesting and relaying data) for layered streaming, and previous works in this area just focus on maximizing the throughput and/or minimizing the packet delay. In this paper, firstly, according to the characteristics caused by layered coding, we propose the four objectives that should be achieved by data scheduling for layered streaming: high throughput, high layer delivery ratio, low useless packets ratio and low subscription jitter; then, we use a 3-stage scheduling approach to request missed blocks, where each stage has different scheduling objective but collaborate with each other. The mincost network flow model, probability decision mechanism and multi-window remedy mechanism are employed in Free Stage, Decision Stage and Remedy Stage, respectively, to achieve the above four goals. Extensive experimental results indicate that our approach outperforms other schemes in both throughput and layer delivery ratio; besides, the useless packets number and subscription jitters are kept low.

Abstract—DHT is a widely used building block for scalable P2P systems. However, as uniform hashing employed in DHTs destroys data locality, it is not a trivial task to support complex queries (e.g., range queries and k-nearest-neighbor queries) in DHT-based P2P systems. In order to support efficient processing of such complex queries, a popular solution is to build indexes on top of the DHT. Unfortunately, existing over-DHT indexing schemes suffer from either query inefficiency or high maintenance cost. In this paper, we propose LIGhtweight Hash Tree (LIGHT)—a query-efficient yet low-maintenance indexing scheme. LIGHT employs a novel naming mechanism and a tree summarization strategy for graceful distribution of its index structure. We show through analysis that it can support various complex queries with near-optimal performance. Extensive experimental results also demonstrate that, compared with state of the art over-DHT indexing schemes, LIGHT saves 50-75 percent of index maintenance cost and substantially improves query performance in terms of both response time and bandwidth consumption. In addition, LIGHT is designed over generic DHTs and hence can be easily implemented and deployed in any DHT-based P2P system. Index Terms—Distributed hash tables, indexing, complex queries. Ç 1