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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

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

Speaker : Bo-Chun Wang

2004.4.21

outline
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results

motivation
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
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
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results

relative work
Relative Work
  • Signal Strength
  • Mobility(direction,speed)
  • History=>probability(user,BS)
shortcoming in previous work
Shortcoming in Previous Work
  • Assumes hexagonal/circular boundary
    • Actual cell boundary fuzzy & irregularly shaped
  • Road topology information not utilized
    • Could potentially yield better accuracy
outline8
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results

advantages of knowing road topology
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

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

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
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

prediction output
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

prediction output14
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

outline21
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results

reservation scheme
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
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?
perfect knowledge over t
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

a more realistic scenario
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
slide26

Under-reservation occurs when predicted order is reversed

Use prediction limits to introduce biases

Choose L & U experimentally

[ctarget, w, tLPL(L), tUPL(U)]

outline30
Outline

。Motivation

。Relative work

。Road topology based mobility prediction

。Dynamic bandwidth reservation scheme

。Simulations and results

simulation model
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
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
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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