BitTorrent Under a Microscope:
Towards Static QoS Provision in
Dynamic Peer-to-Peer Networks
Tom H. Luan*, Xuemin (Sherman) Shen* and Danny H. K. Tsang §
* University of Waterloo
§ Hong Kong University of Science and Technology
BitTorrent (BT): A Brief Introduction
BT, first appeared in October 2002, is a file distribution
system based on the P2P paradigm
Engrosses about 30% of all Internet
traffic volume [1]
Leads to the proliferation of P2P media streaming using
the user-driven data-oriented download approach
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For example, CoolStreaming, PPLive [2] and PPStream for live
and on-demand video streaming
PPlive is reported in [2] to broadcast to over 200,000 users in
one event at the bit rate of 400-800 kbps
Successful media streaming requires providing users with
the static and guaranteed download throughput
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[1]. EContentMag.com, “Chasing the user: The revenue streams of 2006”, December 2005
[2]. Xiaojun Hei, Chao Liang, Jian Liang,Yong Liu and Keith W. Ross, "A Measurement Study of a Large-Scale P2P IPTV System",
IEEE Transactions on Multimedia, vol. 9, no. 8, pp. 1672 - 1687, Dec. 2007.
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BT Under a Microscope
IWQoS’10
QoS in P2P Content Distribution
QoS provisioning is tough in P2P
P2P network is inherently dynamic and heterogeneous
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The heterogeneous bandwidth of peer uploaders results in the
unpredictable download throughput of nodes
The dynamic nature of peer uploaders results in the intense
variance (or jitters) of download throughput to nodes
Problem Statement:
How to accommodate the bandwidth heterogeneity and
dynamics of peers to provision nodes with static and
guaranteed download throughput?
Methodology: Evaluate and enhance the performance of BT
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BT Under a Microscope
IWQoS’10
BT Protocol
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BT strives to ensure (proportional) fairness: Nodes attain the
download rates proportional to their upload rates
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Tit-for-Tat scheme (Forbid freeriders)
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Each node only uploads to others who are
uploading to it
Choking algorithm (Preserve the high-rate
uploaders)
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Incentive mechanism to encourage the upload
Every Tc (e.g., 10) seconds, select nc (e.g, 4)
nodes to unchoke (upload to) among the
peers which are uploading to it
Optimistic unchoke (Explore the high-rate
nodes for data exchange)
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Randomly unchoke no (e.g., 1) node which is not
uploading to it every To (e.g, 30) seconds
BT Under a Microscope
IWQoS’10
Example of the Node Connectivity
Download from others via
optimistic unchoke of others
Upload to others with its
optimistic unchoke
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Data exchange
governed by tit-for-tat
and choking algorithm
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Fixed number of upload
connections
Random number of
download connections
BT Under a Microscope
IWQoS’10
Throughput Analysis of a Random BT Node
Assuming two classess of peers, high bandwidth (H-BW)
and low bandwidth peers
Model the download connections of a randomly tagged
node in class  as a Markov process with state ( X (t ), Y (t ))
 Downloading from x H-BW nodes and y L-BW nodes
c , c Upload capacity of H-BW and L-BW
Download rate at time t
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H
L
nodes, respectively.
N
Asymptotically, the mean and
variance of d (t ) are, respectively,
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Mean population of peers.
pH, pL Portion of H-BW and L-BW nodes,
respectively. pL 1  pH
  ( x, y ) Steady state of the Markov process
and
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BT Under a Microscope
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Numerical Solution
Transition rates are composed of three events
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Dynamic node arrivals and departures
Connections/disconnections due to the choking algorithm
Connections/disconnections due to the optimistic unchoke
Obtain the steady state probability with the balance
equations
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where
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is the transition rate matrix of the node in class
BT Under a Microscope
IWQoS’10
Model Validation
Session level simulator coded in C++
Poisson arrival to the network at the rate of  peers/s
Mean network size to be N
Nodal departure rate    / N
Each experiment with 30 simulation runs and 95%
confidence interval
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BT Under a Microscope
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Download Rate of Tagged Node over Time
Highly dynamic due to peer churns and the frequent
disconnection of choking algorithm and optimistic unchoke
Download rate is proportional to upload rate
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BT Under a Microscope
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Increasing nc and no
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nc: connections in the choking algorithm
no: connections in the optimistic unchoke
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Our model is more accurate to capture the dynamic nature of P2P
Fan, B., Chiu, D.-M., and Lui, J. “Stochastic analysis and file
Increasing nc improves the fairness Fan:
availability enhancement for BT like file sharing systems”, In proc.
Increasing no degrades the fairness of IEEE IWQoS, 2006
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BT Under a Microscope
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Increase Tc and Arrival Rate
Tc : Time interval for executing choking algorithm
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To = 3Tc : Time interval for executing optimistic algorithm
Increasing Tc degrades the fairness as nodes are slow to adapt
Increase arrival rate degrades the fairness as the network becomes
more chaos
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BT Under a Microscope
IWQoS’10
Optimize BT Parameters
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Given the peer arrival rate and mean network size, we
can optimize the parameters of BT towards maximal
fairness as
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Parameters including: number of links and execution frequency
for choking algorithm, and those of optimistic unchoke
Rather than fine tune the parameters, can we improve the
protocol for better performance?
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Enhanced protocol for better QoS provisioning
BT Under a Microscope
IWQoS’10
Node Clustering in BT
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BT relies on node clustering to provision QoS
Nodes of similar upload capacity tend to form clusters to
exchange data
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BT Under a Microscope
IWQoS’10
Protocol Enhancement
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What is wrong with the clustering in BT?
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Optimistic unchoke: blind search
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Randomly connect to nodes in the peer ocean to explore high rate
nodes
Choking algorithm: a trail-and-error manner
Time to locate appropriate cluster peers is long
cluster effect is weak in a highly heterogeneous and dynamic
network
Random walk based peer selection
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Efficiently and fast search cluster nodes
BT Under a Microscope
IWQoS’10
Link Level Homogeneity
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Form the graph in which nodes have equal capacity per
out-degree
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Make outgoing connections of nodes proportional to their
upload capacity
With TCP connection, bandwidth is equally allocated to upload
connections
Random walk algorithm to search peers with high
capacity per out-degree value
Guaranteed fairness: each
connection is bidirectional,
downloading and uploading
at the same rate
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BT Under a Microscope
IWQoS’10
Simulation
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A more heterogeneous network with capacity
distribution
where
 Download rate of the tagged node
over simulation time
 Enhanced BT with random walk
 Approaches to the upload capacity
with vary small variations in the
dynamic network
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BT Under a Microscope
IWQoS’10
Validation of Link-level Homogeneity
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Over 75% of peers have equal
capacity per upload connection,
with the value same to the
analysis
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 Change the upload capacity of the
tagged node every 1000 seconds
 In practice, upload capacity is
shared by multiple applications
BT Under a Microscope
IWQoS’10
Conclusions
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To provision static and accurate QoS guarantee is a
fundamental and important issue for P2P content
distribution networks (e.g., BT, PPStream)
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We propose a Markov model to evaluate the download
rate of a randomly selected BT node
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How to address the network dynamic and heterogeneity
Throughput in the dynamic and heterogeneous network
Describe an enhanced BT protocol with efficient peer
selection using the random walk algorithm
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The Blind trial-and-error search is inefficient
BT Under a Microscope
IWQoS’10
Q&A
Thank You !
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