1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides,...

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1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: http://www.cs.purdue.edu/~fahmy/ Characterizing Overlay Characterizing Overlay Multicast Networks Multicast Networks
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Transcript of 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides,...

Page 1: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

1

Sonia Fahmy and Minseok Kwon

Department of Computer SciencesPurdue University

For slides, technical reports, and implementations, please see:

http://www.cs.purdue.edu/~fahmy/

Characterizing Overlay Characterizing Overlay Multicast NetworksMulticast Networks

Page 2: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

2

Why Overlays?

• Overlay networks help overcome deployment barriers to network-level solutions

• The advantages of overlays include flexibility, adaptivity, and ease of deployment

• Applications• Application-level multicast (e.g., End

System Multicast/Narada)• Inter-domain routing pathology solutions

(e.g., Resilient Overlay Networks)• Content distribution • Peer-to-peer networks

Page 3: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

3

Overlay Multicast

Overlay link

Source

Routers and underlying links

Receivers

Page 4: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Why Characterize Overlays?

• Overlay multicast consumes additional network bandwidth and increases latency over IP multicast quantify the overlay performance penalty

• Little work has been done on characterizing overlay multicast tree structure, especially large trees

• Such characterization gives insight into overlay properties and their causes, and a deeper understanding of different overlay multicast approaches better overlay design

Real data fromESM experiments Simulations Analytical

models

Characterizing Overlay Networks

Page 5: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Our Hypothesis

• Observations• Many high degree high bandwidth routers heavily

utilized in upper levels of ESM/TAG trees, which tend to be longer. Many hosts are connected to lower degree low bandwidth routers, clustered close together at lower levels of the trees. This lowers multicast cost

• Causes• Topology (power-law/small-world)• Overlay host distribution• Overlay protocol (full/partial info/overhead,

delay/bandwidth/diameter/degree, source-based/shared tree)

Page 6: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Overlay Tree Metrics

• Overlay cost = number of underlying hops traversed by every overlay link

• Link stress = total number of identical copies of a packet over the same underlying link

• Overlay cost = ∑stress(i) for all router-to-router links i• Number of hops and delays between parent and child hosts

in an overlay tree• Degree of hosts = host contribution to the link stress of the

host-to-first-router link• Degree of routers and hop-by-hop delays of underlying links

traversed by overlay links• Mean bottleneck bandwidth between the source and

receivers • Relative Delay Penalty (RDP), mean/longest latency

Page 7: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

7

Metrics: Examples

• Overlay cost = 12• Link stress on A = 2• RDP of B = (15+15+10)/20 = 2

Overlay link

Source

Receivers

AB

15 ms 15 ms

10 ms

20 ms

C

Page 8: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

8

Overlay Tree Structure

• Questions• What do overlay multicast trees look like? Why?• How much additional cost do they incur over IP multicast?

• Methodology• Use overlay trees (65 hosts) in ESM experiments (from

CMU) in November 2002. Use public traceroute servers and synthesize approximate routes. (Most university hosts are connected to the Internet 2 backbone network)

• PlanetLab experiments and tree/traceroute data

Page 9: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

9

Results: End System Multicast

• Number of hops between two hosts versus level of host in overlay trees

• Distributions of per-hop delay for different overlay tree levels

(a) Tree level 1

(b) Tree levels 4-6

Page 10: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Overlay Tree Structure: Simulations

• Topologies• Contains 4 thousand routers connected in ways consistent with

router-level power-law and small-world properties• GT-ITM topology with 4 thousand routers• Delays and bandwidths according to realistic distributions

• Overlay multicast algorithms• ESM (End System Multicast) [SIGCOMM 2001]

• A host has the upper degree bound (we use 6) on the number of its neighbors

• TAG (Topology-Aware Grouping) [extended NOSSDAV 2002]• Uses ulimit=6 and bwthresh=100 kbps for partial path matching

• MDDBST (Minimum Diameter Degree-Bounded Spanning Tree) [NOSSDAV 2001, INFOCOM 2003]

• Minimizes the number of hops in the longest path, and bounds the degree of hosts in overlay trees (degree bound = edge bw/min bw)

Page 11: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Results: Number of Hops

• Uniform host distribution• Non-uniform host

distribution

MDDBST less clear than ESM because it minimizes max. cost

Page 12: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Results: Isolation of Topology Effects

• Router degrees • Clustering (small world)

Page 13: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Results: Latency and Bandwidth• Relative delay penalty (RDP)

ESM achieves a good balance, but scalability is a concern

• Mean bottleneck bandwidth

Page 14: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Overlay Multicast Tree Cost• Network Model

• LO(h,k,n) denotes overlay cost for an overlay O when n is the number of hosts

• We only count hops in router subsequences

• We use n instead of m• Why an underlying tree model?

• Simple analysis• Consistency with real topologies

[Radoslavov00]• Transformation from a graph to a k-ary

tree with minimum cost tree

• Why least cost tree?

• Modeling and analysis are simplified

• Many overlay multicast algorithms optimize a delay-related metric, which is typically also optimized by underlying intra-domain routing protocols

• A lower bound on the overlay tree cost can be computed

h

k

Source

Host Receiver

Page 15: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Network Models with Unary Nodes

Self-similar Tree Model (k=2, θ=1, h=3)

1)( ihk

Unary node with only one child

Number of unary nodes created between

adjacent nodes at levels i-1 and i

Branching node

• To incorporate the number-of-hops distribution, use a self-similar tree model [SODA2002]

Page 16: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Receivers at Leaf Nodes

k

Source

αh

(a)

α

k

Level l

(b)

Overlay link

Receiver

))1(1( nkk

h

i

ihk1

)(

)1(2 lhk

1))1(1( )1( nlkk

Page 17: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Receivers at Leaf Nodes

))1(1(1

)( nh

i

ih kkk

0

)1))1(1((2)(

)1()1( nllh kkklg

1))1(1( )1( nlkk

1

)(h

l

l lgk

1

)())1(1(1

1),,(

h

l

lnh

o lgkkkk

knkhL

The overlay cost in (a):

The overlay cost in (b):

where

if otherwise

The sum of (a) and (b)

n1-θ is observed

where

2

1log

1

h

k

kh

Page 18: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Receivers at Leaf Nodes

),(

),,(),,(

khU

nkhLnkhR

o

oo where

h

i

iho kkhU

1

)(),(

θ=0.15

Page 19: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Receivers at Leaf or Non-leaf Nodes

1

1

k

kkM

β

… …

……

kp k(1-p)

Lυ(h-1,k,n)

L υ(h-2,k,n)L υ(h-3,k,n)

h

k(1-p)kp

kp k(1-p)

(a)

nMp )1(1 1 α

β

kp k(1-p)

……

……

kpLevel l

)1(2 )1( kpk lh

)1()(2 lhlh kk (A)

(B)

)()()1( BAlhB

(b)

)1()1(),,1(

)1()(

lTpknklhkpL

lhBlT

Page 20: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Receivers at Leaf or Non-leaf Nodes

)),,1(( )1( nkhLkkp h

))1(1)(122()1( )1( niih kkpkkihB

)},,1()1({)1()1(1

1

nkihkpLihBpkTh

i

ii

1

1

)1(

)},,1()1({)1(

)),,1((),,(h

i

ii

h

nkihkpLihBpk

nkhLkkpnkhL

The overlay cost in (a):

The overlay cost in (b):

where

The sum of (a) and (b)

Page 21: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Receivers at Leaf or Non-leaf Nodes

),(

),,(),,(

khU

nkhLnkhR

where

l

i

ihh

l

l kkM

khU1

)(

1

1),(

θ=0.15

Page 22: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Cost Model Validation

• The analytical results are validated using traceroute-based simulation topologies and our earlier topologies

• Normalized overly cost via simulations

• ESM and MDDBST have n0.8-n0.9; TAG has a slightly higher cost due to partial path matching

• Cost with GT-ITM/uniform hosts is slightly higher than with power-law/small-world

• The normalized overlay tree cost for the real ESM tree is n0.945

Page 23: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Related Work

• Chuang and Sirbu (1998) found that the ratio between the total number of multicast links and the average unicast path length exhibits a power-law (m0.8)

• Chalmers and Almeroth (2001) found the ratio to be around m0.7 and multicast trees have a high frequency of unary nodes

• Phillips et al.(1999), Adjih et al.(2002) and Mieghem et al.(2001) mathematically model the efficiency of IP multicast

• Radoslavov (2000) characterized real and generated topologies with respect to neighborhood size growth, robustness, and increase in path lengths due to link failure. They analyzed the impact of topology on heuristic overlay multicast strategies

• Jin and Bestavros (2002) have shown that both Internet AS-level and router-level graphs exhibit small-world behavior. They also outlined how small-world behavior affects the overlay multicast tree size

• Overlay multicast algorithms include End System Multicast (2000,2001), CAN-based multicast (2002), MDDBST (2001,2003), TAG (2001), etc.

Page 24: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Conclusions

• We have investigated the efficiency of overlay multicast using theoretical models, experimental data, and simulations. We find that: The number of routers/delay between parent and

child hosts tends to decrease as the level of the host in the ESM/TAG overlay tree increaseslower cost

Routing features in overlay multicast protocols, non-uniform host distribution, along with power-law and small-world topology characteristics contribute to these phenomena

We can quantify potential bandwidth savings of overlay multicast compared to unicast (n0.9 < n) and the bandwidth penalty of overlay multicast compared to IP multicast (n0.9 > n0.8)

Page 25: 1 Sonia Fahmy and Minseok Kwon Department of Computer Sciences Purdue University For slides, technical reports, and implementations, please see: fahmy

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Ongoing Work

• We are conducting larger scale simulations and experimental data analysis using PlanetLab.

• We are examining other and more dynamic metrics with other overlay protocols, e.g., NICE, Hypercast

• We will precisely formulate the relationship between the overlay trees, overlay protocols and Internet topology characteristics

• We are investigating the possibility of inter-overlay cooperation to further reduce the overlay performance penalty