NETWORK TOMOGRAPHY TO ENHANCE THE

PERFORMANCE OF SOFTWARE DEFINED

NETWORK MONITORING AND MANAGEMENT

K M Sabidur Rahman with Chaitrali Joshi and Tanjila Ahmed (ECS 273)

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Agenda

•Network Tomography and SDN

•MiniNet Data Collection

•EM algorithm

•Results from EM implementation in R

•Future work

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Network Tomography

“It is the study of a network’s internal characteristics using information

derived from end point data.” - Wikipedia

• Statistical theory and algorithms are used to estimate internal

characteristics of the network topology

• Flexibility of SDN can be used to make better results

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Shortcomings of current measurement methods

• Impractical to measure packet delays at every router

• Proprietary routers are inflexible

• Geographic separation of routers

• Storing packet information at every node is expensive

• Memory constraints

• Causes congestion in communication

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Experimental Setup

• Topology setup using Mininet

• Single source multiple

receiver

• Controller for SDN

• Python based POX

remote controller

S2

H2 S1

S3

H3 H4

H1

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EM Algorithm

•Iterative method for estimation of parameters in a statistical model

•It estimates the maximum likelihood of parameters

•Where the model depends on unobserved latent variable

•E step: Update the conditional expectation(log likelihood) of the parameter

by the given observation

•M step: Find the parameter that maximizes that quantity

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EM Algorithm y = observed end-to-end delay data z = unobserved link delay(latent variable) p=probability of delays on link i

Complete data likelihood can be factorized as :

where we have to estimate and z from end-to-end delay y

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EM Algorithm Complete data likelihood is dependent on likelihood of z as conditional pmf of y given z does not have p parameter.

Where ,number of packets that faces delay j on link i

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EM Algorithm

E Step :

M step:

This is our updated estimate of Pij.

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Results

0

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Data Link 1

EM

Nu

mb

er o

f p

acke

ts

Delay (ms)

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Results

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Data Link 2

EM Link 2

Nu

mb

er o

f p

acke

ts

Delay (ms)

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Results

0

5

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Data Link 3

EM

Nu

mb

er o

f p

acke

ts

Delay (ms)

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Future

•Use more data 100,1000,2000

•Use more complex topology

•Use SDN control mechanism to find the minimum measurement needed for

a network

•Explore temporal effects on delays

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