Arun Venkataramani
Donald Towsley
Presented by: Shiqi Chen, Ionut Trestian
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Late 90s client-server architectures
dominated data transfers on Internet
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Alternatives emerged:
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Unstructured p2p file sharing
Content Distribution Networks
Structured Distributed Hash Tables
Publish subscribe
End-System Multicast
Main point: make data location Independent
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Problems with existing p2p systems
◦ Free riding
◦ Central point of failure (BitTorrent)
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Simple and robust incentive strategy (tit-fortat) is a deterrent for free riding.
Can swarms form the basis of a universal
architecture for the Internet and if so what is
an appropriate architecture?
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Fundamental difference
◦ Uswarm (one huge swarm for all data transfers)
◦ BitTorrent (one swarm per file)
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Typical transfer multipoint-to-point
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Data is location independent and self-verifying
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Designed to send bulk data but can send
dynamic data too.
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Intent Resolution Service – translating intent
(what a peer is looking for, URL, RSS feed) to
metadata
IRS, Modern search engine, web server that
serves metadata
Metadata Resolution Service returns set of
peer addresses (tracker in BitTorrent),
distributed here.
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Peers translate metadata to addresses(3 ways)
◦ Logically centralized tracking service similar to DNS
◦ In-network support for tracking (gateway router
intercepts and processes resolution requests)
◦ Peer-to-Peer tracking
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Centralized trackers suited for pull data
transfer but not fur push data transfer.
Enables location based caching
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Peers have roles depending on their economic
relationship with their peers and network
service provider.
Some peers always ready to send data, social
network based trust possible.
Live streaming – p2p live streaming
Semi-autonomous peer system – push
contents to set-top boxes
Human-centric applications – facilitates push
based applications
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Fundamental benefits of uswarm over
isolated swarms
◦ Post-popularity – BitTorrent robust to flash crowds
but treats bad unpopular content.
◦ Block-availability - Allow peers to change blocks
across different content.
◦ Robust tracking – BitTorrent is inherently
unscalable. Fractured content
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Download capacity
O(log n) greater
Also more robust
to failures
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BitTorrent – central server (single point of
failure)
Low tracker availability is a significant
problem for users.
Solutions
◦ Replicated trackers
◦ Integration of DHTs with BitTorrent clients.
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Our approach, a combination of:
◦ Massively replicated tracking.
 Similar to DNS (hierarchical)
◦ Peer-to-peer gossip.
 Controlled flooding
 Active gossip
◦ In-network tracking.
 Couples a uswarm tracker with in-network caches.
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Traffic engineering
Today’s Internet constraints the routing
choice of both end users and ISPs
Bring ISPs into the picture (tracker router):
return a set of peers that result in the most
load-balanced traffic assignment.
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More complex scenarios required.
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Which replicated tracking mechanism is best
suited.
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Implicitly assumed that download rate is the
performance metric. For some applications
this is not the case.
In-network caching raises the question of
placement and replacement strategies.
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Incentives in isolated swarms
BitTorrent is not robust to selfish peer behavior
Bittyrant: selfish algorithm benefits every peer
irrespective of how many peers are using it.
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Open questions:
Estimating peer upload and download capacities
Analyzing if the proposed mechanism is strategy
proof
Robustness to byzantine faulty peers
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Data plane: extend Bittyrant algorithm – select
peers so as to maximize download on
available upload rate
Users may upload blocks from different files to
download a particular file or simultaneously
download several files with different utility.
Sort peers according to dp/up weighted by
utility
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Control plane
tit-for-tat: keep track of the number of
metadata requests a neighbor helps resolve.
Peers choose to help neighbors that have
been most useful in the past.
Dynamic topology adaptation: peers prefer
other peers with similar content interest for
neighbors, resembling a semantic social
network.
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How to measure the performance of control
plane?
Peer selection in the data plane at fine time scales.
Peer selection in the control plane that operates
over slower time scales
Movement of peers across interest clusters based
on their content access pattern.
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Opening a connection has cost.
So S will not benefit even
he increase the number
of connections if we charge
a fixed cost per connection.
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tit-for-tat: Pairwise Nash equilibrium exists but
the loss of efficiency is unbounded.
If considering routing topology and congestion
control, then Nash equilibrium only exists for
simple topologies and the loss of efficiency can
be arbitrarily large.
Goal: Interactive strategic peer selection while
taking topology and allocation cost into
account.
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Pricing: upload bandwidth may not be free or even
linearly priced.
Indirect trading: agents with low upload capacity may
appoint other agents to participate in uswarm on its
behalf. P2P detour routing may be implemented as a
service on top of uswarm.
Workload and network conditions: Block availability,
TCP’s inefficiency, block-based tit-for-tat strategy,
noisy information on the efficiency or vulnerability.
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DoI-resistant information dissemination service – if
a user seeks a file at least one copy of which exists
in the network then she could be able to retrieve it
unless the underlying network is physically
partitioned by faulty or malicious nodes.
Basic idea: to use massive replication to ensure
that a peer can reach at least one replica.
Knowledge of routing topology: select neighbors
Replicating content: DoS attacks do not make
information unavailable.
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Instrument a small number of Bittyrant clients
to passively monitor transfer performance
and contribute measurement.
It is incentive-compatible for peers to
contribute measurements because peers with
more information about the capacity of other
peers can make better strategic choices.
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uswarm is tolerant to delays or interrupted pointto-point connections by design.
RAPID (Resource Allocation Protocol for Intentional
DTN routing): enables sophisticated knobs to
intentionally optimize performance metrics of
interest.
Push-based application: advertising and trading of
content according to individual interest.
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Model single-swarm and multi-swarm behavior
accounting for strategic peer behavior.
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Topology adaptation model and implementation
of DoI-resistant dissemination service.
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Implement a modified socket API to enable
application use. Investigate interaction with
traffic engineering and virtualized architectures.
Test for security.
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Enable a robust dissemination service
resistant to denial of information attacks.
Foster the growth of novel human-centric
applications.
Enable delay-tolerant data transfer for poorly
connected environments.
Thank you !
Questions ?