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New Models and Algorithms for Active Networks

New Models and Algorithms for Active Networks

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New Models and Algorithms for Active Networks. The Active Bell-Labs Engine. An adjunct active engine to any COTS router Only some packets are diverted to the AE Packet Delay depends on whether it passes thru the AE. Processing time in the AE may depend on data in the packet. - PowerPoint PPT Presentation

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Page 1: New Models and Algorithms for Active Networks

New Models and Algorithms for Active Networks

Page 2: New Models and Algorithms for Active Networks

2

The Active Bell-Labs Engine• An adjunct active engine

to any COTS router

• Only some packets are diverted to the AE Packet

• Delay depends on whether it passes thru the AE.

• Processing time in the AE may depend on– data in the packet.– soft state in the AE.

MIB

routerfilter

Active Engine (AE)

manager

session 1 session 2

Page 3: New Models and Algorithms for Active Networks

3

Addressing Modes

• Explicit - sent directly to a known AE.– efficient

• Oblivious - sent along a path, and intercepted by the first AE en-route.– topology learning – robust

Page 4: New Models and Algorithms for Active Networks

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• What is the right model to analyze algorithmic solutions?

• How to compare the strength of AN architectures?• Are active networks efficient?

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Standard Asynchronous Model

• Communication is between neighbors

• A message arrivals triggers computation at a node

• A single bound on the delay of a communication + computation cycle– What does O(n log n) mean?

Page 6: New Models and Algorithms for Active Networks

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A New Model

• Two bounds on the delay:– C thru the FF.

– P(k) thru the EE.

• Forwarding is done according to the destination addr.

• No assumptions on the routing.

• We use P(k) = P ·k

FF

Execution Environment

(EE)

Filter oracle

forwarding

Page 7: New Models and Algorithms for Active Networks

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DARPA Model vs. Our Model

NodeOS

EE

1

class

FF

Execution Environment

(EE)

Filter oracle

forwarding

EE

2

EE

3

IP

Page 8: New Models and Algorithms for Active Networks

8

Performance Measures

• Communication (Message) complexity - hops traveled by messages

• Time complexity - time to mission completion.

• processing complexity - CPU time used.

Page 9: New Models and Algorithms for Active Networks

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An Application Example:Route Exploration

• In the model - a node is only aware of its local neighbors.

• A node wishes to learn the route to some destination.

• Abstraction of the traceroute program.

45

Page 10: New Models and Algorithms for Active Networks

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A naïve Solution

• The source query nodes sequentially.

• O(n2) messages.• O(n2C+nP) time.

Page 11: New Models and Algorithms for Active Networks

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A naïve Solution

• The source query nodes sequentially.

• O(n2) messages.• O(n2C+nP) time.

Page 12: New Models and Algorithms for Active Networks

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report-en-route

• A query process advances sequentially.

• Reports are sent to the source for each query.

• O(n2) messages.• O(nC+nP) time.

send Report(id, c+1) to sif id send MSG*(s,d, c+1) to d

Page 13: New Models and Algorithms for Active Networks

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collect-en-route

• A query process advances sequentially.

• Information is collected in the forward direction, and sent by the destination to the source.

• O(n) messages.• O(nC+n2P) time.

Page 14: New Models and Algorithms for Active Networks

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collect-en-route

if i==d send Report(list|i) to selse send MSG*(s,d, list|i) to d

Page 15: New Models and Algorithms for Active Networks

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Route ExplorationReport

En-RouteCollectEn-Route

naive

time nP+nC n2P+nC nP+n2C

message n2 n n2

Can we do better?

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Report-every-l• Obtain the route length.

• Initiate collect-en-route in n/l segments of length l.

Page 17: New Models and Algorithms for Active Networks

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Report-every-l• Complexities:

– message O(n2/l)– time O(nC+(n+l2)P)

• alg. at the ith segment starts after (i-1)(C+P)l

• segment time cmplx:

• For l=n2/3:– message O(n4/3); time O(nC+ n4/3 P)

)/()( 2/

1

lnOillln

i

PllCiPCl

i

2

1

)(

Page 18: New Models and Algorithms for Active Networks

18

Collect-rec• Optimal up to a log factor !

• Obtain the route length.• Partition the route to two segments.• Send results from the second segment using the

FF.• Perform recursively.• Complexities:

– message O(n log n); time O(nC+nP)

Page 19: New Models and Algorithms for Active Networks

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Collect-rec (2)

Time: O(nP+nC)

Message: O(nlogn)

Page 20: New Models and Algorithms for Active Networks

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Collect-rec (2)

Time: O(nP+nC)

Message: O(nlogn)

Page 21: New Models and Algorithms for Active Networks

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Collect-rec complexity

• We can count messages/time per iteration.

• Alternative approach:– TC(n) TC(n/2) + 4n(P+C)– MC(n) 2MC(n/2) + 4n

Page 22: New Models and Algorithms for Active Networks

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Route Exploration (5)

Naive CollectEn-Route

ReportEn-Route

ReportEvery-l

CollectRec

time nP+n2C nP+2nC nP+2nC ll22PP++ nnCC nnPP++nnCC

message n2 n n2 nn22//ll nn lloogg nn

Page 23: New Models and Algorithms for Active Networks

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• A message for a large number of receivers.

• No notion of group. Ad-hoc.

• Processing time is linear in the recipient size.

• Example: a full binary tree

Message Dissemination

Page 24: New Models and Algorithms for Active Networks

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Naïve solution

• send a message to each recipient

• Complexity for a full binary tree– time: nP+log n C– message: n log n

Page 25: New Models and Algorithms for Active Networks

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Mail Distribution (2)

1 2 3 4 5 6 7 8receivers

sender

5,6,7,8,m

7,8,m

8,m7,m

5,6,m

1,2,3,4,m

Page 26: New Models and Algorithms for Active Networks

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Naïve solution

• send a message to each recipient

• Complexity for a full binary tree– time: nP+log n C– message: n log n

Active

2nP+log n C

2n

Page 27: New Models and Algorithms for Active Networks

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Multicast

• We assume a multicast group exist

• Aim: build the best tree

• In general: NP-hard

• We will look at the line case

Page 28: New Models and Algorithms for Active Networks

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Previous Solutions

• Unicast:– time complexity: O(n(P+C))– message complexity: O(n2)

• message dissemination:– time complexity: O(n(P+C))– message complexity: O(n)

Page 29: New Models and Algorithms for Active Networks

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Better solution

• Embed a tree in the line

• What should be its arrity?

Page 30: New Models and Algorithms for Active Networks

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Complexity of a tree scheme

nCnPx

Cnxxx

xnnPxnTC

x

nTCC

x

xnPxnTC

nn

xnMC

x

nxMC

nx

x

nxMCi

x

nnMC

x

x

x

x

i

log)1(

1...

111

)1(log)1()(

)1()1()(

log2

)1()(

2

)1()(

2

1

1

Page 31: New Models and Algorithms for Active Networks

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Optimum

• x / log x achieves optimum at 3 when restricted to integers

2 4 6 8220

240

260

280

300

tree degree

tim

e

2 4 6 8150

160

170

180

190

200

210

220

tree degree

mes

sag

e

C=1, P=20

Page 32: New Models and Algorithms for Active Networks

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Other Basic Problems

• Bottleneck detection - computation along a route.

• Message dissemination to an ad-hoc group.

• Topology discovery.

• Computation of a global function.

Page 33: New Models and Algorithms for Active Networks

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Summary

• A new model to analyze active network applications.

• Can be used for Other domains– Peer2Peer– application layer multicast

• Can be used to compare strength of architectures by comparing lower bounds.

Page 34: New Models and Algorithms for Active Networks

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Paper(s) available at:

www.cs.bell-labs.com/~ABLE