School of Electrical Engineering Telecommunications UNSW Cost-effective Broadcast for Fully Decentralized Peer-to-peer Networks Marius Portmann Aruna

School of Electrical Engineering &

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Cost-effective Broadcast for Fully Decentralized Peer-to-peer Networks

Marius Portmann & Aruna Seneviratne


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Peer to Peer Systems• Two types

– Structured•Guarantee location of content (if exists)•Access within bounded number of hopsControl of data placements and topology

– Unstructured•Decentalized•Looser guaranteesPlacement of data and topology is ad-hoc


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Wireless Environments• Characterized by

– Highly transient node populations– Wide range of users form non cooperating

organizations– Searches on partial information– Not typically looking for “rare” information

– replicated at a number of places• Not a good match for structured

systems – Back to unstructured systems


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Unstructured Systems• Most widely used application of

p2p systems is file sharing– As the placement of data is ad-hoc

• Only random searchers are possible• Hard to find desired files without wide

distribution of queries• Unscalable unless can improve the

efficiency of searches


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Example - Gnutella• Gnutella can be considered as “pure”

peer-to-peer system – Fully decentralized and distributed searching

• Operation of Gnutella– Two types of services

• Searching for files • Peer discovery

– Implemented with application level broadcasts

– Broadcast is implemented with TTL flooding


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File Location• A query message is forwarded to all its

neighbors, except for the one, where it was received from

• Each message has a Time To Live (TTL) – Decremented by one at each visited node – Message is dropped when TTL=0

• Each message has an unique ID • Node keeps a record of IDs of messages

that it has seen in the recent past – Message with the same ID and type as ones

that that have been received are dropped


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Cost Metric 1• Define a cost metric for

comparison of methods– number of messages that are

generated and forwarded – based solely on the network size and

the average node degree, • Estimate the average bandwidth

consumption per node

Calzone

i would not mention cost metric 1.I think in the paper there is only cost metric 2.(in a old version of the paper I had two cost metrics)maybe just delete this slide


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Cost Metric 2

network in the nodes ofnumber :Ni nodeby forwarded messages ofnumber :

broadcast aby reached nodes ofnumber :

1 1

i

N

ii

mr

mr

c

Calzone

Maybe you can say that the cost c is the average number of messages that need to be forwarded per node reached in a broadcast.


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Flooding - Unscalable• Resource consumption per node of

flooding based broadcast can be prohibitively high, even for networks of moderate size


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Rumor Mongering or Gossip Protocols

• A class of probabilistic protocols for message routing

• Messages are spread in a network much like a disease in a susceptible population. (epidemiological protocol)

• The neighbors to which messages are forwarded to by each node are chosen randomly.

• Trades off reliability and speed for a reduction in cost


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Blind Counter Rumor Mongering

• A node n initiates a broadcast – Send the message m to B neighbors,

chosen at random– When a node (p) receives a message m

from anther node (q)• If (p has received m no more than F times)• p sends m to B uniformly randomly chosen

neighbors that p knows have not yet seen m– p knows if its neighbor q has already seen the

message m only if p has sent it to q previously, or if p received the message from q


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Cost of BCRM• Difficult to obtain analytical

expressions to describe the behavior of a Gossip protocol, even for relatively simple topologies

• Can give an upper limit – bounded by BF- an upper limit for

the cost c


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Simulation Results• Barabási Topology:

– Model for generating topology is based on how typical p2p networks evolve

– Power-law characteristics• 1000 nodes with an average node

degree of 6 – F and B for the BCRM was set to be 2


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Some More Results

• Trade-off of cost, reliability and time by choosing F and B appropriately

• Level of cost reduction depends on the average node degree– The higher the node degree is, the bigger

the potential for cost reduction


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P2P Network Topologies• Typical characteristic of peer-to-peer networks

is a power-law distribution of the node degrees– most nodes have few links while a small number of

nodes have a large number of links

From Matei Ripeanu & Ian Foster


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Deterministic Rumor Mongering

• Make intelligent decisions as to which of its neighbors to forward messages to

• Based it on the node degree of the corresponding nodes– The nodes with the lowest degree are

chosen first


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Deterministic Rumor Mongering cont.

• When a node p receives a message m from node q

– If (p has received m no more than F times)

1) send m to all of its neighbors of degree one, and

2) B of the rest of its neighbors with the lowest node degree, that p knows have not yet seen m


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Rationale for (1)• Pendant neighbors, have no other

chance to receive the message• These pendant neighbors cannot

contribute to the further propagation of the message – not considered for the limit of B

messages to be forwarded


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Rationale for (2)• Nodes of high degree receive a large

number of copies of the same message– This overhead grows approximately linearly

with the node degree– Also with higher parameters B and F.

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100 120

Node Degree

Mes

sage

s Re

ceiv

ed

B=3, F=2

B=2, F=2

B=2, F=1


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Viability• The only requirement is that each node

knows the node degree of its immediate neighbors

• Not in conflict with the decentralized nature of the networks – Can easily be integrated– Gnutella

• a one byte field in the Gnutella message header • Increasing the minimal message size by less than

5%.


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Some Results

Performance of Deterministic Rumor Mongering compared to Blind Counter Rumor Mongering

• For a given B and F, DRM achieves a significant higher reach than the BCRM, within a shorter time

• For a given reach, DRM has a significantly lower cost

B Freach time cost c reach time cost c

2 1 67.7% 23.2 2.00 96.10% 21.1 2.003 1 86.9% 17.1 2.65 99.00% 16.4 2.602 2 91.7% 21.6 2.78 99.80% 18.4 2.822 3 97.1% 19.9 3.17 100.00% 18.1 3.303 2 97.7% 15.3 3.41 100.00% 14.2 3.423 3 99.2% 14.4 3.73 100.00% 14.0 3.76

BCRM DRM

Calzone

The main point here is that a given reach (%) can be achieve with DRM much cheaper than with BCRM.For example, we want to reach >96% of the network, with BCRM we choose B=2, F=3 and the resulting cost is 3.17. With DRM we choose B=2, F=1, and the resulting cost is 2.


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(3,2)(3,3)

(2,3)(2,2)(3,1)

(2,1)

(3,2)(2,3)

(3,3)

(2,2)(3,1)

(2,1)

00.5

11.5

22.5

33.5

44.5

5

60 70 80 90 100

Reach (%)

Cos

t per

Nod

e re

ache

dSome More Results

BCRM DRM

(B,F)

Calzone

This repeats the last point from the previous slide.the little triangle, at coordinates x=100 y=5 represents the Gnutella protocol with flooding.(with a average node degree of 6 each node sends it to all its neighbours except the one it received it from -> 5)


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Conclusions• Unstructured peer-to-peer systems are more

suitable for wireless environments• For unstructured systems to be viable,

scalable methods of searching need to developed

• The obvious way of is to look at alternatives to broadcast

• One such scheme that have been used in the past in other application is Rumor Mongering (Gossiping)

• We show that, Rumor Mongering, can be used as a basis for providing an alternative flooding for distributing queries in unstructured peer to peer systems

Calzone

We not only show that we can use RM, we introduce DRM, which is a new scheme that has better performance (in the context of p2p) than 'normal' Rumor Mongering protocols


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More InformationAvailable form mobqos.ee.unsw.edu.au

M. Portmann, Pipat Sookavatna, Sebstien Ardon and Aruna Seneviratne,”The Cost of Peer Discovery and Searching in the Gnutella Peer-to-peer File Sharing Protocol”, IEEE ICON 2001, Bangkok, September 2001M. Portmann, and Aruna Seneviratne, “The Cost of Application-level Broadcast in a fully Decentralized Peer-to-peer Networks”, ISCC, Italy, July 2002M. Portmann, and Aruna Seneviratne, “Cost-effective Broadcast for Fully Decentralized Peer-to-peer Networks”, accepted for publication, Computer Communication, Special Issue on Ubiquitous Computing

Also related workQin Lv, Sylvia Ratnasamy and Scott Shenker,”Can Heterogeneity Make Gnutella Scalable?”, 1st International Workshop on Peer-to-Peer Systems (IPTPS '02), Cambridge, MA, USA, March 2002Berverly Yang, and Hector Garcia-Molina,”Efficient Search in Peer-to-Peer Networks”, 1st International Workshop on Peer-to-Peer Systems (IPTPS '02), Cambridge, MA, USA, March 2002


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School of Electrical Engineering Telecommunications UNSW Cost-effective Broadcast for Fully Decentralized Peer-to-peer Networks Marius Portmann Aruna