Swarm-based peer-to-peer streaming (SPS) mechanisms tend to generate a significant amount of costly inter-ISP traffic. Localization of overlay connectivity reduces inter-ISP traffic. However, it can adversely affect the delivered quality. In this paper, we systematically examine the performance of SPS for live video over localized overlays. We identify and discuss the fundamental bottlenecks limiting the stream quality and present OLIVES, an ISP-friendly P2P streaming mechanism for live video. OLIVES maintains a fully localized overlay to reduce the volume of inter-ISP traffic and incorporates a two-tier inter-ISP and intra-ISP scheduling scheme to maximize the delivered quality to individual peers. One important design choice is to perform basic scheduling at a substream level and to use implicit coordination among peers. This allows OLIVES to efficiently detect missing blocks and pull them into the ISP in a timely manner with a minimum in coordination overhead. Furthermore, OLIVES incorporates a shortcutting technique that limits the buffer requirements for each participating peer and effectively reduced the playout latency. Through analysis and extensive simulations, we demonstrate the ability of OLIVES to deliver high-quality streams over localized overlays in various realistic scenarios.

We measure Web performance bottlenecks in home broadband access networks and evaluate ways to mitigate these bottlenecks with caching within home networks. We first measure Web performance bottlenecks to nine popular Web sites from more than 5,000 broadband access networks and demonstrate that when the downstream throughput of the access link exceeds about 16 Mbits/s, latency is the main bottleneck for Web page load time. Next, we use a router-based Web measurement tool, Mirage, to deconstruct Web page load time into its constituent components (DNS lookup, TCP connection setup, object download) and show that simple latency optimizations can yield significant improvements in overall page load times. We then present a case for placing a cache in the home network and deploy three common optimizations: DNS caching, TCP connection caching, and content caching. We show that caching only DNS and TCP connections yields significant improvements in page load time, even when the user's browser is already performing similar independent optimizations. Finally, we use traces from real homes to demonstrate how prefetching DNS and TCP connections for popular sites in a home-router cache can achieve faster page load times.

We present the first large-scale analysis of Web performance bottlenecks as measured from broadband access networks, using data collected from extensive home router deployments. We analyze the limits of throughput on improving Web performance and identify the contribution of critical factors such as DNS lookups and TCP connection establishment to Web page load times. We find that, as broadband speeds continue to increase, other factors such as TCP connection setup time, server response time, and network latency are often dominant performance bottlenecks. Thus, realizing a "faster Web" requires not only higher download throughput, but also optimizations to reduce both client and server-side latency.

No abstract available.

This paper presents a new approach to determine the geographical footprint of individual Autonomous Systems that directly provide service to end-users, i.e., eyeball ASes. The key idea is to leverage the geo-location of end-users associated with an eyeball AS to identify its geographical footprint. We leverage the kernel density estimation method to estimate the density of users across individual eyeball ASes. This method enables us to cope with the potential error associated with the location of individual end-users while controlling the level of aggregation among data points to capture a geo-footprint at the desired resolution. We use the resulting geo-footprint of individual eyeball ASes to identify their likely Point-of-Presence (PoP) locations. To demonstrate our proposed technique, we use the inferred geo-locations of 48 million users from three popular P2P applications and assess the geo- and PoP-level footprints of 1233 eyeball ASes. The validation of the identified PoP locations by our technique against online information and prior results by a commonly-used technique based on traceroute shows a very high accuracy. Leveraging the acquired PoP locations, we examine the implications of geo-footprint of eyeball ASes on their connectivity to the rest of the Internet. In particular, we present a case study that reveals a much more complex picture of AS-level connectivity as compared to what the more traditional but geography-agnostic BGP- or traceroute-based approaches depict.

In Swarm-based Peer-to-Peer Streaming (SPS) mechanisms, par-ticipating peers form a randomly connected mesh over which they incorporate swarm-like content delivery. In practice, a subset of participating peers may form clusters in the overlay due to vari-ous reasons such as localization of connectivity within edge ISPs. Despite the commonly held assumptions, the appearance of such clusters could significantly degrade the delivered quality to partici-pating peers in SPS mechanisms. This paper examines the effect of overlay clustering on the per-formance of SPS mechanisms for live content. Leveraging the no-tion of two-phase content delivery in SPS mechanisms, we illus-trate the effect of overlay clustering on content delivery. We pro-pose the Overlay Monitoring and Repair (OMR) mechanism as a distributed and scalable approach to maintain proper overlay con-nectivity in SPS mechanisms. The key idea is to use delivered quality to individual peers as an indication of poor connectivity from other regions of the overlay. OMR employs a probabilistic ap-proach to ensure an adequate number of properly-positioned peers reacts to detected clustering in the overlay without any coordina-tion. Reacting peers rewire a small number of carefully-selected connections in the overlay to significantly improve the performance of content delivery. Our preliminary evaluations demonstrate that OMR mechanism can achieve its goals.

Abstract — Peer-to-Peer (P2P) streaming mechanism is a promising approach to offer one-to-many distribution of live streaming content to large number of residential users across the Internet. While a few P2P streaming mechanisms have been recently proposed, the behavior of these mechanisms in sessions where a large fraction of uasers are residential peers have not been examined. Several characteristics of residential users could affect the behavior of P2P streaming sessions including (i) the heterogeneity of access link bandwidth, (ii) the limitation of available resources due to asymmetric nature of access link bandwidth (for DSL and cable modem), and (iii) the participation of free-loaders. In this paper, we examine the effect of these three characteristics of residential users on the performance of P2P streaming mechanisms using ns simulations. We show that these characteristics could adversely affect the performance of P2P streaming mechanisms as follows. First, the delivered quality to individual users is not correlated with their contributed resource to the system. Second, the presence of free-loaders could dramatically degrade the delivered quality to participating peers even when the amount of available resources in the system are adequate. Our findings suggest that P2P streaming has to address these issues in order to be successfully deployed among residential users. I.

The success of swarming content delivery has motivated a new approach to live peer-to-peer (P2P) streaming that we call mesh-based streaming. In this approach, participating peers form a random mesh and incorporate swarming content delivery to stream live content. Despite the growing popularity of this approach, neither the design tradeoffs nor the basic performance bottlenecks in mesh-based P2P streaming are well understood. This paper presents PRIME, the first mesh-based P2P streaming for live content that effectively incorporates swarming content delivery. We identify two performance bottlenecks in a mesh-based P2P streaming, namely bandwidth bottleneck and content bottleneck. We derive proper peer connectivity to minimize bandwidth bottleneck as well as an efficient pattern of delivery for live content over a random mesh to minimize content bottleneck. We show that the pattern of delivery can be divided into diffusion and swarming phases and then identify proper packet scheduling algorithm at individual peers. Using ns simulations, we examine key characteristics, design tradeoffs and the relationship between main system parameters.

Existing approaches to P2P streaming can be divided into two general classes: (i)tree-based approachesuse push-based content delivery over multiple tree-shaped overlays, and (ii)mesh-based approachesuse swarming content delivery over a randomly connected mesh. Previous studies have often focused on a particular P2P streaming mechanism and no comparison between these two classes has been conducted. In this paper, we compare and contrast the performance of representative protocols from each class using simulations. We identify the similarities and differences between these two approaches. Furthermore, we separately examine the behavior of content delivery and overlay construction mechanisms for both approaches in static and dynamic scenarios. Our results indicate that the mesh-based approach consistently exhibits a superior performance over the tree-based approach. We also show that the main factors attributing in the inferior performance of the tree-based approach are (i) the static mapping of content to a particular tree, and (ii) the placement of each peer as an internal node in one tree and as a leaf in all other trees.

A common approach to peer-to-peer (P2P) streaming is to form a tree-based overlay coupled with push content delivery. This approach cannot effectively utilize the outgoing bandwidth of participating peers, and therefore it is not self-scaling. In contrast, swarm-like content delivery mechanisms exhibit the self-scaling property but incorporating them into live P2P streaming applications are challenging for two reasons: (i) in-time requirement of content delivery and (ii) the limited availability of future content.