69 research outputs found
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 peerās 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 BUCSāTRā2001ā017, 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
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
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