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Myconet: A Fungi-Inspired Model forP2P Superpeer Overlay Topologies

Paul Snyder, Rachel Greenstadt, and Giuseppe Valetto

{pls29,greenie,valetto}@cs.drexel.edu

Department of Computer ScienceDrexel University

Outline

• Overview• Protocol description• Evaluation• Conclusion

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Myconet: Self-organization of superpeer overlay topologies

• Self-organizing unstructured P2P overlay– Hierarchical superpeers

• Inspired by hyphae, the robust, root-like structures of fungal mycelia

• Goals– Effective exploitation of peers– Resilience to failures

Photo credit: K. Fleming.Reproduced under a Creative Commons license.http://www.flickr.com/photos/myriorama/101120710/

Quick Definitions

• Peer-to-peer• Overlay networks• Superpeers• Unstructured P2P

Myconet’s Metaphor

Mycelium

Hyphae

Nutrients/Biomass

Myconet overlay

Superpeers

Regular peers

Goals of the Myconet Protocol

• Peers operate with local information only• Use multiple protocol states to balance

exploration and exploitation• Select highest-capacity nodes as

superpeers• Quick recovery after node failure

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Outline

• Overview• Protocol description• Evaluation• Conclusion

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Myconet Basics

• Round-based simulation in PeerSim• Peers characterized by an integer capacity• Peers with direct hyphal links are

considered neighbors• Uses a lower-level overlay to

communicate node status information– The gossip-based Newscast protocol

3. loses parent hypha

1. s

pore

s

START

attachedbiomass

unattachedbiomass

extendinghypha

2. finds hypha

• All peers begin as disconnected biomass

• Peers that cannot find a hypha to connect to become extending hyphae (superpeers)

• Extending hyphae seek biomass and to connect to another hyphal peer

Protocol: Extending Hyphae

Protocol: Bootstrapping

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Biomass peersExtending hyphae

Round 0

Protocol: Bootstrapping

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Biomass peersExtending hyphae

Round 1

Protocol: Branching Hyphae• Extending hyphae with

enough biomass promote to branching hyphae, which:– Form inter-hyphal

connections– Absorb biomass from

extending peers– Regulate number of

extending peers in the network

– Demote to extending status if unable to maintain biomass

3. loses parent hypha

1. s

pore

s

5. reaches or

exceeds capacity

6. absorbed

7. falls below

full utilization

7. promoted by a branching

or immobile hypha

START

attachedbiomass

unattachedbiomass

branchinghypha

extendinghypha

2. finds hypha

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Protocol: Superpeer Promotion

1313

Biomass peersExtending hyphaeBranching hyphae

Round 1

Protocol: Superpeer Promotion

1414

Biomass peersExtending hyphaeBranching hyphae

Round 2

Protocol: Superpeer Promotion

1515

Biomass peersExtending hyphaeBranching hyphae

Round 4

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immobilehypha

3. loses parent hypha

1. s

pore

s

5. reaches or

exceeds capacity

6. absorbed

8. absorbed

7. falls below

full utilization

7. promoted by a branching

or immobile hypha

10. falls belowutilization threshold

9. reaches orexceeds target

hyphal link count

START

11.

abso

rbed

attachedbiomass

unattachedbiomass

branchinghypha

extendinghypha

2. finds hypha

• Branching hypha with Cn hyphal connections become immobile hyphae– In the network long

enough to be considered stable

– Pull biomass from extending and branching hyphae

– Maintain hyphal connections if lost

– Regulate growth or collapse of extending and branching hyphae

– Demote if unable to maintain utilization threshholds

Protocol: Immobile Hyphae

Protocol: Stability

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Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 4

Protocol: Stability

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Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 17

Protocol: Stability

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Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 22

Outline

• Overview• Protocol description• Evaluation• Conclusion

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Evaluation

1. Convergence to stable configuration

2. Resource utilization

3. Approximation of optimal superpeer configuration

4. Resilience to catastrophic failures

Evaluation: Methodology

• Tested using round-based simulation in PeerSim• Most graphs represent experimental results for networks

of 105 nodes, averaged over 25 runs– Experiments were conducted with network sizes from 103 to 106

nodes• Peer capacities were assigned using a power-law

distribution– For networks of size of 105, the probability of peer n having

capacity x is P[cn = x] = x-2, with x in the interval [1,500]– Maximum capacities were adjusted for other network sizes– Also tested with uniform random distributions, with similar results

• Compared performance to SG-1 and ERASP

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Evaluation: Time to Stability

For 105 nodes, Myconet quickly converges to around 225 superpeers

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Evaluation: Utilization Levels

Within 20 rounds, 95% of peers are connected to a branching or immobile hypha

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Evaluation: Superpeer Configuration

The total superpeer count closely tracks the theoretical optimum

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Evaluation: Failure Recovery

Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 22

Evaluation: Failure Recovery

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Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 39

Evaluation: Failure Recovery

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Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 40

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Evaluation: Failure Recovery

Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 57

Evaluation: Failure Recovery

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Biomass peersExtending hyphaeBranching hyphaeImmobile hyphae

Round 71

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Evaluation: Failure Recovery

The Myconet overlay quickly repairs itself after a catastrophic failure

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Evaluation: Bottom Line

• Myconet effectively constructs and maintains a strongly-interconnected, decentralized superpeer overlay

• Quickly converges to an optimal number of superpeers and high levels of capacity utilization.

• Performance scales smoothly up to at least 106 peers• Compared to other the state of the art, our simulations

show Myconet fares well in terms of:– Network stabilization– Response to catastrophic failure– Capacity utilization

Outline

• Overview• Protocol description• Evaluation• Conclusion

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Conclusions

• Myconet overlay demonstrates applicability of fungal metaphor to peer-to-peer overlays

• Take-aways:– Hierarchical superpeer states were useful in

designing self-organizing network dynamics– Choosing to underutilize some superpeers (extending

hyphae) useful when balancing exploration vs. exploitation

– Increasing Cn parameter increased instant resistance to disconnection, but had unexpectedly slight effects on dynamics

Future Work

• Examine performance under network churn• Measure overlay maintenance costs• Test the performance of P2P applications

running on the Myconet overlay• Dynamic adaptation of Cn parameter• Move from round-based simulation to

protocol implementation• Explore possibility of formalizing metaphor in

terms of more rigorous biological models

Questions?

Paul Snyder, Rachel Greenstadt, and Giuseppe Valetto{pls29,greenie,valetto}@cs.drexel.edu

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References

[1] A. Montresor, “A robust protocol for building superpeer overlay topologies” in Proceedings of the 4th International Conference on Peer-to-Peer computing. Zurich, Switzerland: IEEE, Aug. 2004, CONFERENCE, pp. 202-209.

[2] W. Liu, J. Yu, J. Song, X. Lan, and B. Cao, “ERASP: An Efficient and Robust Adaptive Superpeer Overlay Network,” Lecture Notes in Computer Science, vol. 4976, p.468, 2008.