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Dynamic Bandwidth Reservation in Cellular Networks Using Road Topology Based Mobility Predictions InfoCom 2004. Speaker : Bo-Chun Wang 2004.4.21. Outline. 。 Motivation 。Relative work 。Road topology based mobility prediction 。Dynamic bandwidth reservation scheme 。Simulations and results.

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Slide1 l.jpg

Dynamic Bandwidth Reservation inCellular Networks Using Road Topology Based Mobility PredictionsInfoCom 2004

Speaker : Bo-Chun Wang

2004.4.21


Outline l.jpg
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results


Motivation l.jpg
Motivation

Forced termination

is worse than blocking

a new call !!

Insufficient bandwidth

Forced termination

i.e., handoff “dropped”

  • Prioritize handoffs by reserving bandwidth

    • Tradeoff  more news calls blocked


Motivation4 l.jpg
Motivation

PFT = Forced termination probability

PCB = New call blocking probability

Static: PFT = 0.01, PCB =0.15

Reservation

Dynamic: PFT = 0.01, PCB = 0.10

time

  • Handoff arrivals are random

    • Dynamic reservation more efficient

  • No knowledge of future: use prediction

    • Accuracy   reservation efficiency 


Outline5 l.jpg
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results


Relative work l.jpg
Relative Work

  • Signal Strength

  • Mobility(direction,speed)

  • History=>probability(user,BS)


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Shortcoming in Previous Work

  • Assumes hexagonal/circular boundary

    • Actual cell boundary fuzzy & irregularly shaped

  • Road topology information not utilized

    • Could potentially yield better accuracy


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Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results


Advantages of knowing road topology l.jpg
Advantages of KnowingRoad Topology

Candidate Cell A

Candidate Cell B

Handoff regions

Reserve more in Cell A!

Probability 0.1

Probability 0.9

Where to reserve bandwidth?


Preliminaries l.jpg

B

A

Road segment (A,B)

Preliminaries

  • Each BS keeps a database of the roads within its coverage area

    • Roads are divided into “road segments”

    • Topology extracted from digital maps


Database entries l.jpg

All segments

Handoff-probable

segments only

Database Entries

  • For each road segment:

    • Neighboring segments

    • Transition probability to each neighbor

    • Statistical data:

      • Transit time

      • Probability of handoff

      • Time spent before handoff

      • Handoff locations

      • Target handoff cell


Modeling segment transition l.jpg
Modeling Segment-transition

  • Transition between road segments modeled as 2nd order Markov processes

F

F

D

D

E

E

MT1 & MT2 have different probabilities of entering EF

MT1

MT1

C

C

MT2

MT2

B

B

J

J

I

I

A

A


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Prediction Output

[ctarget, w, tLPL(L), tUPL(U)]

4-tuple:

Lower prediction limit

Predicted target handoff cell

Upper prediction limit

Prediction weight

Derived using previously observed prediction errors

Time tLPL(L):P [actual handoff time  tLPL(L)] = L

Time tUPL(U):P [actual handoff time  tUPL(U)] = U


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Prediction Output

Can have multiple 4-tuples per MT

[ctarget, w, tLPL(L), tUPL(U)]

4-tuple:

(One for each possible path to each handoff region)

Handoff region

w

  • ctarget: Target cell if handoff occurs on EF

  • w:P(ABBEEF, handoff at EF)

  • tLPL(L), tUPL(U): Prediction limits of time from handoff if ABBEEF occurs

F

D

E

pdf of time

from handoff

C

B

A








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Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results


Reservation scheme l.jpg
Reservation Scheme

Two processes:

1) Compute Rtarget periodically: using predictions falling within the next T

2) Adapt T : to achieve desired PFT

arrival

time

t0

t0+T

departure

T PFT


Logic behind the scheme l.jpg
Logic Behind the Scheme

Suppose:

  • Have precise handoff information

    Question:

  • How much bandwidth should we reserve to prevent any incoming handoff from being dropped within T?


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Perfect Knowledge Over T

Bandwidth change due to incoming/ outgoing handoffs

Time T

Rtarget increases monotonically with T

2

1

0

time

1

T PFT

Sum of

bandwidth changes

Control PFT by adjusting T

Peak=1

1

Set Rtarget to peak

0

time

1


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A More Realistic Scenario

  • Previous example assumes perfect knowledge of handoff timings

  • Examine a more realistic scenario: only predictions available

    • Prediction errors in handoff timings


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Under-reservation occurs when predicted order is reversed

Use prediction limits to introduce biases

Choose L & U experimentally

[ctarget, w, tLPL(L), tUPL(U)]


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Adjusting Tthreshold at each BS


Adjusting t threshold at each bs28 l.jpg
Adjusting Tthreshold at each BS


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Adjusting Rtarget at each BS


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Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results


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Simulation Model

  • 19 wireless cells

  • Randomly generated roads

  • Uncertain handoff regions

  • Traffic lights

  • Capacity = 100 BUs

  • Voice (1 BU) & video (4 BUs) calls


Other schemes for comparison l.jpg
Other Schemes for Comparison

  • Benchmark:knows MT’s nextcell & handoff time

  • Static:fixed reservation target

  • Reactive:reacts to forced terminations

  • Choi’s AC1:uses MT’s previous cell, & time in current cell

  • LE:linear extrapolation (Infocom’01)

  • RTB with Path Knowledge (RTB_PK):knows future path




Summary l.jpg
Summary

  • Mobility predictions incorporate both positioning info & road topology knowledge

    • No cell geometry assumption

  • Adaptive reservations use both incoming & outgoing handoff predictions

  • Prediction accuracy, reservation efficiency

    • Lesser new call blocking while meeting handoff prioritization target


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