Bootstrapping in Gnutella: A Preliminary Measurement Study

To join an unstructured peer-to-peer network like Gnutella, peers have to execute a bootstrapping function in which they discover other on-line peers and connect to them. Until this bootstrapping step is complete, a peer cannot participate in file sharing activities. Once bootstrapping is complete, a peer’s experience is strongly influenced by the choice of neighbor peers resulting from the bootstrapping step. Despite its importance, there has been very little attention devoted to understanding the behavior of this bootstrapping function. In this paper, we study the bootstrapping process of a peer in the Gnutella network. This is a preliminary investigation, consisting of 1) an analysis and performance comparison of bootstrapping algorithms of four Gnutella servent implementations, 2) a measurement-based characterization of the global Gnutella Web Caching System (GWebCaches), a primary component of the current bootstrapping functions, and 3) a study of the behavior and experience of a single GWebCache that was setup locally and made part of the global caching infrastructure. Our study highlights the importance of understanding the performance of the bootstrapping function as an integral part of a peer-to-peer system. We find that 1) there is considerable variation among various servent implementations that correlates to their bootstrapping performance, 2) even though the GWebCache system is designed to operate as a truly distributed system in keeping with the peer-to-peer system philosophy, it actually operates more like a centralized infrastructure function, and 3) the GWebCache system is subject to misreporting of peer and cache availability due to stale data and absence of validity checks

Proceedings of the Sixth International Workshop on Web Caching and Content Distribution

OVERVIEW The International Web Content Caching and Distribution Workshop (WCW) is a premiere technical meeting for researchers and practitioners interested in all aspects of content caching, distribution and delivery on the Internet. The 2001 WCW meeting was held on the Boston University Campus. Building on the successes of the five previous WCW meetings, WCW01 featured a strong technical program and record participation from leading researchers and practitioners in the field. This report includes all the technical papers presented at WCW'01. Note: Proceedings of WCW'01 are published by Elsevier. Hardcopies of these proceedings can be purchased through the workshop organizers. As a service to the community, electronic copies of all WCW'01 papers are accessible through Technical Report BUCS‐TR‐2001‐017, available from the Boston University Computer Science Technical Report Archives at http://www.cs.bu.edu/techreps. [Ed.note: URL outdated. Use http://www.bu.edu/cs/research/technical-reports/ or http://hdl.handle.net/2144/1455 in this repository to access the reports.]Cisco Systems; InfoLibria; Measurement Factory Inc; Voler

Travel assistance for ACM SIGCOMM '97 Conference

Issued as final repor

Convex Analytic Method Revisited: Further Optimality Results and Performance of Deterministic Control Policies

The convex analytic method (generalized by Borkar) has proved to be a very versatile method for the study of infinite horizon average cost optimal stochastic control problems. In this paper, we revisit the convex analytic method and make three primary contributions: (i) We present an existence result for controlled Markov models that lack weak continuity of the transition kernel but are strongly continuous in the action variable for every fixed state variable. (ii) For average cost stochastic control problems in standard Borel spaces, while existing results establish the optimality of stationary (possibly randomized) policies, few results are available on the optimality of deterministic policies, and these are under rather restrictive hypotheses. We provide mild conditions under which an average cost optimal stochastic control problem admits optimal solutions that are deterministic and Markov, building upon a study of strategic measures. We also review existing results establishing the optimality of stationary and deterministic policies. (iii) We establish conditions under which the performance under stationary deterministic policies is dense in the set of performance values under randomized stationary policies

Generation and Analysis of Random Graphs to Model Internetworks

Graph models are commonly used in studying solutions to internetworking problems. This paper considers several random graph models that have been used to model internetworks, and considers ways to characterize the properties of these graphs. By matching the characteristics of the random graphs to the characteristics of real internetworks, more accurate modeling can be achieved

Scheduling Uplink Bandwidth in Application-layer Multicast Trees

Many applications can benefit from the use of multicast to distribute content efficiently. Due to the limited deployment of network-layer multicast, several application-layer multicast schemes have been proposed. In these schemes, the nodes in the multicast tree are end systems which are typically connected to the network by a single access link. Transmissions to the children of a node in the multicast tree have to share this single uplink, a factor largely ignored by previous work.In this work, we examine the effect of access link scheduling on the latency of content delivery in a multicast tree. Specifically, we examine the general case where multiple packets (comprising a block of data) are sent to each child in turn. We provide an analytical relation to compute the latency at a node in the multicast tree and show the relationship to the packet size and block size used to transfer data.We propose heuristics for tree construction which take link serialization into account. We evaluate this effect using simulations and experiments on the Planet- Lab network and show that using larger block sizes to transfer data can reduce the average finish time of the nodes in the multicast tree at the expense of slightly increased variance

Scalability Techniques in QoS Routing

One barrier to deployment of large-scale QoS networks is scalability of QoS routing. Two major sources of overhead incurred by QoS routing are frequent network state updates and QoS-based path computation. Researchers have proposed an impressive array of techniques to reduce these overheads. The goal of this paper is to survey scalability techniques, in the context of a taxonomy intended to illustrate the relationships between different approaches and highlight areas of open research. We also include selected performance results from our own work, to demonstrate the inherent tension between scalability and performance. Our results are obtained using simulations of networks with up to 200 nodes; such large topologies are critical for fully evaluating scalability techniques

On Scalable QoS Routing: Performance Evaluation of Topology Aggregation

A number of important questions remain concerning the scalability of networks with quality of service guarantees. We consider one of these questions: can QoS routing scale to large networks? To address this question, we evaluate performance of four QoS routing algorithms both with and without topology aggregation, based on simulations of relatively large, structured networks. Among our observations, we find --- contrary to intuition --- that topology aggregation does not always have a negative impact on routing performance. Aggregation can reduce the routing information fluctuation, increase stability, and thus benefit routing performance. We also propose two new methods of aggregating routing information. Our hybrid aggregation method has performance much better than conventional star aggregation and approaches unaggregated performance. Our weighted aggregation method, while intuitively appealing, offers mixed performance across topologies

An Evolutionary Framework for AS-Level Internet Topology Modeling

Models for network topology form a crucial component in the analysis of protocols. This paper systematically investigates a variety of evolutionary models for autonomous-system (AS) level Internet topology. Evolution-based models produce a topology incrementally, attempting to reflect the growth patterns of the actual topology. While evolutionary models are appealing, they have generally agreed less closely with measurements of real data than non-evolutionary models. We attempt to understand what contributes to a "good" evolutionary model. Our systematic study consists of a relatively generic evolutionary model framework, which we populate with different choices for the components. This allows us to compare a variety of instances of models to measurements from real data sets. We study issues such as the initial topology, the type of preferential connectivity used in adding edges, and the role of "growth" edges added between existing nodes. We find that appropriate instantiation of the framework can provide topologies that agree closely with real data. We also use our work to highlight several crucial open problems in topology modeling