3.2 resource management approach in heterogeneous wireless access networksv1

8/6/2019 3.2 Resource Management Approach in Heterogeneous Wireless Access Networksv1

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Resource Management Approach in

Heterogeneous Wireless Access etworksBased on IEEE1900.4 Architecture

Min ShengThe State Key Lab. of IS & Information Science Institute,

Xidian University

[email protected]


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Introduction and Background Diverse coexisting Radio Access Technologies (RATs) with cognitive

ability are the most important features of future wireless systems,

which form heterogeneous cognitive wireless networks .

Ryan W. Thomas IEEE Communications Magazine December 2006 CognitiveNetworks: Adaptation and Learning to Achieve End-to-End Performance Objectives

A cognitive network is a network with

a cognitive process that can perceivecurrent network conditions, and then

plan, decide and act on those

conditions. The network can learn

from these adaptations and use them

to make future decisions, all while

taking into account end-to-end goals.

OBSERVE

Monitoring

Discovery

PLA

Optimization

ACT

Reconfiguration

Profiles Policies

Context Dicision

GOALS

Feedback- ew Knowledge


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Resource Management Approach under IEEE1900.4 Architecture

Heterogeneous Wireless etwork scenario


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Resource Management Approach under IEEE1900.4 Architecture

Inter-network resource allocation

RA ResourceReservation

Access etwork Selection

RRM


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Inter-network Resource Allocation

Objective of inter-network resource allocation Allocate bandwidth dynamically compatible with the

network environment to a particular service area from

each of the available networks in that service areas so that all of the service providers are satisfied.

When the network environment changes, such as the trafficintensity and the distribution of users, the system resources arereallocated


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Inter-network Resource Allocation B. Maximum etwork Resource Utility In each resource allocation process, we use a utility function of

throughput

Where is the utility of network i for an allocated bandwidth of b

to connection x . Parameters w and are constants indicating thescale and the shape of the utility function .

( ), log( )con

i xU w b =

1B

l

2m

Bm

2B

l

1B

c

2B c

3m

4m

5m

2c

4c

( ),con

i xU

The total available bandwidth in these networks are B m , B

c1 , B c2 , B l1 , and B l2 , respectively. Let m i denote the

amount of bandwidth offered by WMAN to area i , letc2 and c 3 denote bandwidth offered by cellular network

to area 2 and area 3, and let c 4 and c 5 denote bandwidthoffered by cellular network to area 4 and area 5, andlet B l1 and B l2 denote the amount of bandwidth

available from WLANs in area 3 and area 5.

5

1i m

i

m B=

=

2 3 1cc c B+ =

4 5 2cc c B+ =


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Inter-network Resource Allocation The total utility of the entire network can be obtained from

( ) ( )

( ) ( )

2 2 3 3 111 2 3

1 2 3

4 4 5 5 24 5

4 5

log log log

( , )

log log

l

tol i i

l

m c m c Bm

U m c w

m c m c B

+ + + + + = + + + + +

(1)

To maximize total utility, an optimization problem is

formulated as follows:Maximize : ( , )tol i iU m c

Subject to :5

2 3 4 5 21

, ,i m cl ci

m B c c B c c B

=

= + = + =

1 2

2 2 3 4 5 2 2

1 2

3 2 3 4 5 3 1 2 1

1 4

4 2 3 4 5 4 4

51

5 2 3 4 5 5 2 4 2

32

2 2 2 3 1 2 1

0

0

0

0

0

total

m

total

m c l

total

m

total

m c l

total

c l

U

m B m m m m m cU

m B m m m m m B c B

U

m B m m m m m c

U

m B m m m m m B c B

U

c m c m B c B

= =

+ = = + +

= = +

= = + + = =

+ + +

54

4 4 4 5 2 4 2

0total c l

U

c m c m B c B

= = + + +


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RAN Resource Reservation Wiener models have been proven effective in modeling stochastic

processes that are similar in nature to the amount of resourcesrequired for future handoff calls, i.e., stochastic processes wherethe values of the random variables are affected by a large number of independent or weakly dependent factors, each with a relatively

small impact.

( ) ( ) R R t R t t t t = = +

The resources required byhandoff calls in a RAN which is

a stochastic processPrediction timeinterval

standard normalrandom variable

constant parameters

A normal random variable with ( , ).t t


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RAN Resource Reservation CDP handoff call dropping probability

Pr ( ) 1ob R L CDP =

Pr ( ) 1 R u t L u t

ob CDP t t

=

2R ~ N( , )t t ~ (0,1) R u t

t

( )t L L

= + Exp CDP=2%,

CDP=3%

2.3 L t t = +

0.5 L t t = +


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Access Network Selection Based on the current available resource for handoff

connections or new connections, access network selection will be done.

When a connection arrivals, it will select a RAN which has the

maximum residual resource according to current network resource allocation and reservation. If no RANs residualresources are satisfied its requirement, this connection is

rejected by the system.


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Evaluation of proposed solution

1 2 3 4 50.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

N e w

A r r

i v a l

C a

l l D r o p p o

i n g

P r o

b a

b i l i t y

Areas in System

= 14, CRRM = 14, RRM = 28, CRRM = 28, RRM = 42, CRRM = 42, RRM

1 2 3 4 50.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

0.022

0.024

0.026

H a n

d o

f f C a

l l D r o p p

i n g

P r o

b a

b i l i t y

Area in System

= 14, CRRM

= 14, RRM = 28, CRRM = 28, RRM = 42, CRRM = 42, RRM


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Evaluation of proposed solution

56789101112131415

5 6 7 8 9 10 1112 13 14 15

0.5

0.6

0.7

0.8

0.9

1

05

1015

2030

4050

600

0.5

1

1.5

2

2.5

3

3.5

4

x 10 4

Resource utility v.s call arrival rate Total users in system


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Conclusions How to increase the system resource utility is a

challenging problem. Based on the prediction of thehandoff call arrival rate and the variation of traffic indifferent hours, we present a new resource management

approach coordinating with IEEE1900.4 architecture ,which can reserve system resource dynamically and re-allocat for each RAN, so that the performance of systems

is increased. .


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22

T T hh aa nn kk ss !!

3.2 resource management approach in heterogeneous wireless access networksv1

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