turning heterogeneity into an advantage in overlay routing

1

Turning Heterogeneity into an Advantage in Overlay Routing

Gisik Kwon

Dept. of Computer Science and Engineering

Arizona State University

Published in INFOCOM 2003Authors: Ahichen Xu(HP), Mallik Mahalingam(VMware), Magnus Karlsson(HP)

Arizona State University2

Scalable Computing Lab.

Motivation

Exploiting physically efficient routing and peer heterogeneity over DHT-based overlay network

Constructing an auxiliary network – expressway



Default overlay : CAN and eCAN

Each node knows its neighbors in the d-space Forward query to the neighbor that is closest

to the query id Example: assume n1 queries f4

1 2 3 4 5 6 70

1

2

3

4

5

6

7

0

n1 n2

n3 n4n5

f1

f2

f3

f4



AS-2

P2P Network

AS-1

AS-3

Brocade Layer

S R

Original Route

Brocade Route

Brocade Architecture



Expressway

Expressway nodes(EN) & expressway neighbors– Autonomous System(AS) topology– Landmark clustering

Route summary – Propagated periodically – All the local nodes in same AS



Routing

Expressway node Ordinary node



Experiment

Stretch– The ratio of accumulated latency in the actual

routing path to the shortest-path latency from the source to destination

Two topology– Internet-like topology derived from BGP report– Transit-stub graph by GT-ITM

Logical auxiliary– Brocade-like system



Comparison various approaches

AS topology Transit-stub



TTL and Number of ENs

AS topology Transit-stub

10

Efficient Content Location Using Interest-Based Locality in Peer-to-Peer

Systems

Gisik Kwon



Published in INFOCOM 2003Authors: Kunwadee Sripanidkulchai, Bruce Maggs, Hui Zhang (CMU)Excerpt from Kunwadee Sripanidkulchai’s presentatin file



Motivation

Design goals– Decentralized– Simple and robust – Scalable Let’s retain the simplicity and robustness of Gnutella

and make it scalable

• Locality!– Network locality? No.– Popularity? No.– Interest-based locality? Yes.



“If a peer has a particular piece of content that I am interested in, it is very likely that it will have other pieces of content that I am (will be) interested in as well.”

Interest-based locality

2002 Infocom proceedings?

2001 Infocom proceedings?

Random person on the street

Someone in my research group



Overlay on top of Gnutella Benefits

– Can be easily integrated into Gnutella

– Can be used with many other underlying mechanisms like DHT’s

Our solution: Shortcuts



Discover interest-based shortcuts

Where is ? No shortcut.Discover and add shortcut.

Shortcut



Use interest-based shortcuts

Where is ?

Use shortcut. Success!

Shortcut

O(1) scope for most searches.No index (state) maintained.



Constructing shortcuts Shortcut discovery

– Infer locality using underlying protocol (Gnutella)– Add 1 shortcut to list at a time

Shortcut selection– Rank shortcuts based on performance– Ask shortcuts sequentially– Limit shortcut list size to 10



Trace



Performance of IB shortcuts



Removing practical limitations Shortcut discovery

– Add 1 shortcut to list at a time– => add all peers returned from search– => discover shortcut through our existing shortcuts

Shortcut selection– Limit shortcut list size to 10– => no bound



Potential of IB shortcuts

21

Measurement-Based Optimization Techniques for Bandwidth-Demanding

Peer-to-Peer Systems

Gisik Kwon



Published in INFOCOM 2003Authors: T.S.Eugene Ng, Yang-hua Chu, Sanjay G. Rao, Kunwadee Sripanidkulchai, Hui Zhang



Motivation

Improve the performance with light-weight measurement-based techniques

Qualitative analysis

RTT probing – Smallest response to 36B ICMP ping message

10KB TCP probing– Fastest download of 10KB data

Bottleneck bandwidth probing(BNBW)– Largest nettimer– Nettimer is a project to do end-to-end network performance

measurement. – It can listen passively to existing network traffic or actively

probe the network.



Performance metrics

Media file sharing– Optimality Ratio (OR)

The ration between the TCP bandwidth achieved by downloading from the selected server peer and the TCP bandwidth achievable from the best server peer in the candidate set

Overlay multicast streaming– Convergence time

The amount of time after the initial join it takes for the peer to receive more than 95% of the stable bandwidth for 30 seconds

stable bandwidth is determined based on the bandwidth it receives at the end of a 5-minutes experiment



Host properties



Accuracy of choices

36B RTT 10KB TCP BNBW



Average OR

CMU 10Mbps UIUC



Average OR

CMU ADSL U of Alberta



Media file sharing

Joint ranking



Overlay multicast streaming

RTT– Single packet RTT probing

RTT filter + 10K– At most 5 best RTT -> 10KB downloading

RTT filter + 1-bit BNBW– At most 5 best RTT -> highest bottleneck BW



Mean receiver BW



Convergence time

Basic techniques Combined techniques

turning heterogeneity into an advantage in overlay routing

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