Sajjad FIT'11

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MCDM Method and Semantics Integration forUnified Communication Management and Control

Sajjad Ali Musthaq, Christophe Lohr, Annie Gravey

Department of Computer Engineering

Telecom Bretagne Brest, France


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Motivations

- Which access provides the bestQoS with least cost?

FIT 2011, Islamabad Pakistan

Project Stackholder:

Partners: Alcatel, Comverse and Telecom Bretagne

Company m@ges

Company m@ges


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Introduction We are at frontiers between

private-public network border How to manage ressources

in multi-service, multi-vendorsand multi-homedenvironnement ?

Traffic management issues atthe private-public border.

Call Server and Session BorderController are the mainelements.



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Outlines


Proposed Architecture

Multi Criteria Decision Making (MCDM)

Grey Relational Analysis (GRA) and its Application Over

the Proposed Platform System Model Regarding the Problem

Ontology Integration with MCDM.

Test Bed for the Validation of the Proposed Solution.

Conclusion


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Proposed

Architecture

-Call Server-Handles registration,user profile and servicemanagement.-Performs profile related

CAC

-Session Border Controller-Performs NAT/PATtranslation-Handles ressources related

CAC-Analyzes SIP/SDP-Acts as PolicyEnforcement Point(PEP)


Control Plane

SBC

Mobile operator

3G

Call Server

SDSL router

ADSL router

ADSL router(limited)

Operator Hot Spot3G

FAI1

Policy server

DSLAM

DSLAM

DSLAM

SIP/IP flow

SNMP flow

Data traffic

MONA sub-project

VPN SIP Client

SIP client

Service plane

Proxy/FW

Reverse proxy

SIP client

SIP client

Application data traffic

(HTTP, SNMP, streaming HTTP, proprietary )

SIP/media

Network/Transport plane


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-We have introduced PolicyServer (PS)-Decision Engine within PSprovides dynamic/efficient

control and managementWhile taking into accountdynamic and static info



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Goals, Criteria, Objectives



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Multi Criteria Decision Making (MCDM)

Problems of decision making might involvemultiple objectives and goals. For example:

Locating a nuclear power plant involves objectives such as:

- Safety

- Health

- Environment

- Cost

- FaultLine (Evolution after Japan Incident)



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Multi Criteria Decision Making (MCDM) and the

Decision Engine

Several Criteria Link Profiles

User Profiles

Business Objectives

Attributes extracted from the context

A Multi-criteria, Multi-Attribute and Multi-objective

problem has to be addressed.



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MCDM Method Application

Figuring out the Goals, Criteria, And Alternatives.

Hierarchy Construction

Decision Matrix

Utility Function

Mathematical Steps

to rank/grade the links



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Grey Relational Analysis Method

Reference Vector (Link benchmark) construction from

context and platform conditions

Normalization of the Decision Matrix

Normalization of the Reference Vector (RV) Finding the distance between the corresponding entities in

DM and RV

Calculating Grey Relational Coefficients (GRC)s

Finding the weights of the Criteria elementsWeighted normalized GRC matrix



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Inter/ Intra Plane Semantics, Variations



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Ontology


Service Profile

Voice

Service

Video

Service

Service

Parameter

Operational

Parameter

Service-specific

Parameter

QoSAttribute

Measurable

Attribute

Physical

Attribute

Metric Unit

SLA Service

Provider

QoS

MetricViolation Availability Reliability Charging

Methodology

Threshold Aggregation Performance

Bandwidth Physical

supportssupports

offers

Service Ontology

QoS Ontology

SLA Ontology Model


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Modules of Policy Server Framework



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Test Bed to Validate the Solution



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Application Of GRA Over the Test Bed


UR Utilization Ratio

D Delay

J Jitter

PL Packet Loss

TB Total Bandwidth

AB AvailableBandwidth


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Observations (Throughput)


Higher throughput

Better resource utilization

1 2 3 40

1

2

3

4

5

6

7

8

9

10x 10 7

Links

B

its/s

Total Capacity of Each Link in Bits/s

Throughput W ithout Decis ion Engine

Throughput W ith De cis ion Eng ine


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Observations (Call Dropping Probability)


Lower call dropping


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Observations (Delay)


The cost of the rise in throughput and decrease in CDP is an add-on

delay


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Conclusions

The proposed decision engine accommodates multiple

goals, criteria, sub criteria and alternatives.

Dynamic variations and fluctuations are being taken into

account while computing decision.

Semantics are being captured by integrating Ontology

with MCDM.

The system offers better throughput with an add-on delay

Call Dropping Probability (CDP) for routing decisions

computed via the system is lower than the built-in Load

Balancer (LB).



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Thank YouFor Questions please contact

[email protected]


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Sajjad FIT'11