Abstract—Peer-to-peer streaming systems are becoming highly popular for IP Television (IPTV). Most systems can be categorized as either tree-based or mesh-based, and as either pushbased or pull-based. However, there is a lack of clear understanding of how these different mechanisms perform comparatively in a real-world setting. In this paper, we compare two representative streaming systems using mesh-based and multiple tree-based overlay routing through deployments on the PlanetLab widearea experimentation platform. To the best of our knowledge, this is the first study to directly compare streaming overlay architectures in real Internet settings. Our results indicate that mesh-based systems inject a much higher number of duplicate packets into the network, but they perform better under a variety of conditions. In particular, mesh-based systems give consistently higher application goodput when the number of overlay nodes, or the streaming rates increase. They also perform better under churn and large flash crowds. Their performance suffers when latencies among peers are high, however. Overall, mesh-based systems appear to be a better choice than multi-tree based systems for peer-to-peer streaming at a large scale. I.

Abstract—A number of network path delay, loss, or bandwidth inference mechanisms have been proposed over the past decade. Concurrently, several network measurement services have been deployed over the Internet and intranets. We consider inference mechanisms that use O(n) end-to-end measurements to predict the O(n 2) end-to-end pairwise measurements among n nodes, and investigate when it is beneficial to use them in measurement services. In particular, we address the following questions: (1) For which measurement request patterns would using an inference mechanism be advantageous? (2) How does a measurement service determine the set of hosts that should utilize inference mechanisms, as opposed to those that are better served using direct end-to-end measurements? We explore three solutions that identify groups of hosts which are likely to benefit from inference. We compare these solutions in terms of effectiveness and algorithmic complexity. Results with synthetic datasets and datasets from a popular peer-to-peer system demonstrate that our techniques accurately identify host subsets that benefit from inference, in significantly less time than an algorithm that identifies optimal subsets. The measurement savings are large when measurement request patterns exhibit small-world characteristics, which is often the case. 1 Index Terms—Internet measurement, delay inference 1

Several overlay-based live multimedia streaming platforms have been proposed in the recent peer-to-peer streaming literature. In most of the cases, the overlay neighbors are chosen randomly for robustness of the overlay. However, this causes nodes that are distant in terms of proximity in the underlying physical network to become neighbors, and thus data travels unnecessary distances before reaching the destination. For efficiency of bulk data transmission like multimedia streaming, the overlay neighborhood should resemble the proximity in the underlying network. In this paper, we exploit the proximity and redundancy properties of a recently proposed clique-based clustered overlay network, named eQuus, to build efficient as well as robust overlays for multimedia stream dissemination. To combine the efficiency of content pushing over tree structured overlays and the robustness of data-driven mesh overlays, higher capacity stable nodes are organized in tree structure to carry the long haul traffic and less stable nodes with intermittent presence are organized in localized meshes. The overlay construction and fault-recovery procedures are explained in details. Simulation study demonstrates the good locality propoerties of the platform. The outage time and control overhead induced by the failure recovery mechanism are minimal as demonstrated by the analysis. 1.

In most large-scale peer-to-peer (P2P) applications, it is necessary to collect vital statistics data — sometimes referred to as logs — from up to millions of peers. Traditional solutions involve sending large volumes of such data to centralized logging servers, which are not scalable. In addition, they may not be able to retrieve statistics data from departed peers in dynamic peer-to-peer systems. In this paper, we solve this dilemma through an indirect collection mechanism that distributes data using random network coding across the network, from which servers proactively pull such statistics. By buffering data in a decentralized fashion with only a small portion of peer resources, we show that our new mechanism provides a “buffering ” zone and a “smoothing ” factor to collect large volumes of statistics, with appropriate resilience to peer dynamics and scalability to a large peer population. 1

Abstract—In large-scale peer-to-peer (P2P) live streaming systems with a limited supply of server bandwidth, increasing the amount of upload bandwidth supplied by peers becomes critically important to the “well being ” of streaming sessions in live channels. Intuitively, two types of peers are preferred to be kept up in a live session: peers that contribute a higher percentage of their upload capacities, and peers that are stable for a long period of time. The fundamental challenge is to identify, and satisfy the needs of, these types of “superior ” peers in a live session, and to achieve this goal with minimum disruption to the traditional pull-based protocols that real-world live streaming protocols use. In this paper, we conduct a comprehensive and in-depth statistical analysis based on more than 130 GB worth of runtime traces from hundreds of streaming channels in a largescale real-world live streaming system, UUSee (among the top three commercial systems in popularity in mainland China). Our objective is to discover critical factors that may influence the longevity and bandwidth contribution ratio of peers, using survival analysis techniques such as the Cox proportional hazards model and the Mantel-Haenszel test. Once these influential factors are found, they can be used to form a superiority index to distill superior peers from the general peer population. The index can be used in any way to favor superior peers, and we simulate the use of a simple ranking mechanism in a natural selection algorithm to show the effectiveness of the index, based on a replay of real-world traces from UUSee. I.

Abstract—Effective network measurement can significantly improve application performance. One of the main challenges in obtaining network measurements is to achieve high accuracy while consuming few network resources. To address this problem, several inference mechanisms have been proposed. These mechanisms can provide the O(n 2) end-to-end measurements among n nodes using O(n) measurements, with some loss in accuracy. We construct a measurement request graph where a measurement request issued by an application (e.g., for delay between two nodes) is represented by an edge between the nodes. When the measurement request graph is sparse, an inference mechanism operating over all the nodes (complete inference) incurs unnecessary cost. Given a measurement request graph, our goal is to optimize the number of measurements as well as improve overall accuracy by applying inference only to dense sub-graphs, while taking the other measurements directly. We call this technique partial inference. Previous work only considered static measurement request graphs. However, the measurement request graph can be dynamic when nodes frequently join and leave the network. This paper designs and evaluates a distributed algorithm where each node decides if it should participate in an inference mechanism based on limited information. I.

Abstract—Television transmitted over IP (IPTV) presents numerous opportunities for users as well as service providers, and has attracted significant interest from business and research communities in recent years. Among the emerging IPTV delivery architectures, the peer-to-peer based delivery mechanism is considered attractive due to the relative ease of service deployment. However, the question of how well P2PTV applications would support a growing number of users has not been fully investigated so far. In this paper, we try to address this question by studying scalability and efficiency factors in a typical P2P based live streaming network. Through the use of the data provided by a production P2PTV system, we carry out simulations whose results show that there are still hurdles to overcome before P2P based live streaming could become widely used. I.

the date of receipt and acceptance should be inserted later Abstract Several overlay-based live multimedia streaming platforms have been proposed in the recent peer-to-peer streaming literature. In most of the cases, the overlay neighbors are chosen randomly for robustness of the overlay. However, this causes nodes that are distant in terms of proximity in the underlying physical network to become neighbors, and thus data travels unnecessary distances before reaching the destination. For efficiency of bulk data transmission like multimedia streaming, the overlay neighborhood should resemble the proximity in the underlying network. In this paper, we exploit the proximity and redundancy properties of a recently proposed clique-based clustered overlay network, named eQuus, to build efficient as well as robust transport overlays for multimedia streaming. To combine the efficiency of content pushing over tree structured overlays and the robustness of data-driven mesh overlays, higher capacity stable nodes are organized in tree structure to carry the long haul traffic and less stable nodes with intermittent presence are organized in localized meshes. The overlay construction

Abstract—A multitude of overlay network designs for resilient routing, multicasting, quality of service, content distribution, storage, and object location have been proposed. Overlay networks offer several attractive features, including ease of deployment, flexibility, adaptivity, and an infrastructure for collaboration among hosts. In this paper, we explore cooperation among coexisting, possibly heterogeneous, overlay networks. We discuss a spectrum of cooperative forwarding and information sharing services, and investigate the associated scalability, heterogeneity, and security problems. Motivated by these services, we design Synergy, a utility-based overlay internetworking architecture that fosters overlay cooperation. Our architecture promotes fair peering relationships to achieve synergism. Results from Internet experiments with cooperative forwarding overlays indicate that our Synergy prototype improves delay, throughput, and loss performance, while maintaining the autonomy and heterogeneity of individual overlay networks. 12 I.

Abstract—Television transmitted over IP (IPTV) presents numerous opportunities for users as well as service providers, and has attracted significant interest from industry as well as research communities in recent years. Among the emerging IPTV delivery architectures, the peer-to-peer based delivery mechanism is considered attractive due to the relative ease of service deployment and potential bandwidth savings. However, the question of how well P2PTV networks would support a growing number of users has not been fully investigated so far. In this paper, we try to address this question by studying scalability and efficiency factors in a typical P2P based live streaming network. Through the use of the data provided by a production P2PTV network, we carry out simulations whose results show that there are still hurdles to overcome before P2P based live streaming could become widely deployed. Index Terms—P2PTV, overlay network, peer churn, peer selection. I.