Jiwoong LeeUniversity of California, Berkeley

Zero Collision Random Backoff Algorithm

EE228A High speed Comm Networks

May 2 2006

2/28

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

Motivating Problem:Motivating Problem:Shared wireless medium Shared wireless medium -- How is the effect of Collision ?How is the effect of Collision ?

Example— Bechtel Engineering Library

— Some event driven-distributed sensor networks

EarthquakeSurveillance

Throughput

Size

100%

79% Theoretical limit

802.11family

3/28

Research Initiative QuestionResearch Initiative Question

Environment— In a fully distributed random access network— Without any central coordinated function

Will it be possible to build a — Zero Collision Probability Random Access

Backoff Algorithm ?

!!

BSS

(with BS)

Source/Target PairCollision DomainNetwork

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

4/28

TerminologyTerminology

Size of a network: # of current members

Capacity of a network: Max # of supportable members

Backoff slot: Allowed slot to start to access the medium

Contention Window: Available backoff slots

p-Persistency: transmission with prabability p when allowed

Chatty station: high p

Shy station: low p

Bursty station: p goes up and down

Member station: associated with BS. BS is a member.

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

5/28

Two Principles of the ZeroCollision MACTwo Principles of the ZeroCollision MACRelaxing the infinite Soft capacity constraint

– cf. Statistical Multiplexing Infinite soft capacity

— Physical systems’ Hard capacity limit802.11 family: Beacon TIM Partial Virtual BitmapHandles max 2008 associations

— Performance limitAs the network size grows

— Coverage limit802.11a: 20m range, 802.11b: 100m range, 802.11g: 50m range

This is an important observation. The small range of transmission guarantees small propagation delay and small delay spread, reducing the chance of carrier sensing error.

Sibley Auditorium: 40 laptop users among 250 attendees— User’s Mobility Pattern

No new extra join/leave at least for a few minutes

Learning— Each station remembers history of past successful transmission

and collision (Deterministic / Statistic)

CW=81st Contention

CW=162nd

No Learning

Learning

CW=83rd

STA1STA2

STA1STA2

…

…CW=8 CW=8 CW=8

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

6/28

Conventional diagram of the Backoff procedure

A Key Observation: Sufficient Statistic for Access(from each station’s point of view)

— Idle slots (Stations actively count them)

— First slot of transmission

Modeling: Backoff procedureModeling: Backoff procedure

CW

…………

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

7/28

Modeling: Backoff MatrixModeling: Backoff MatrixCW=8 fixed. CW=8 fixed.

Each station has— Self vector— Neighbor vector— Pointer vector

— Backoff Matrix

Operation— At each Idle slot: 1 unit

Cyclic Right Shift of P

— eg.

0 0 0 1 0 0 0 00 0 1 0 0 1 0 01 0 0 0 0 0 0 0

⎡ ⎤ ⎡ ⎤⎢ ⎥ ⎢ ⎥= =⎢ ⎥ ⎢ ⎥⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎣ ⎦

SB N

P

[1 0 0 0 0 0 0 0]=P

[0 0 0 1 0 0 0 0]=S[0 0 1 0 0 1 0 0]=N

↑

st

nd

On initialization, [0] [1 0 0 0 0 0 0 0]After 1 idle slot, [1] [0 1 0 0 0 0 0 0]After 2 idle slot, [2] [0 0 1 0 0 0 0 0]

=

=

=

PPP

1[ 1] [ ] Tn n+ =P P C

1

0 1 0 00 0 1 0 00 0 1 0 00 0 1 0 00 0 1 0 00 0 1 00 0 11 0 0

T

⎡ ⎤⎢ ⎥⎢ ⎥⎢ ⎥⎢ ⎥⎢ ⎥= ⎢ ⎥⎢ ⎥⎢ ⎥⎢ ⎥⎢ ⎥⎢ ⎥⎣ ⎦

C

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

8/28

Modeling: Problem StatementModeling: Problem Statement

Station is allowed to transmit when

Collision criterion— Local criterion:

Not exact. Suboptimal— Global criterion:

Exact. Optimal

We avoid Global criterion since— Exactness ← Global knowledge← Central Coordination

— However, I will show later that a network using local criterion for the zero collision in medium access will converge to one which is using global criterion

Now, we reduce the original fuzzy problem into two specific problems— Q. How to update N ?— Q. How to select S given N ?— Many subproblems will be defined one by one

0 or 0T T T⋅ > >S P N P S N

0T >S P

0M M

T Ti i j j

i j i≠⋅ >∑∑S P S P

??

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

9/28

Modeling: FormalizationModeling: Formalization

Scheduling Dynamics— Whenever idleslot is sensed

Zero Collision Lemma— A network achieves Zero Collision iff

1[ 1] [ ][ 1] ( [ ], [ ], )[ 1] ( [ ], [ ], )

Ti i

i i i

i i i

n nn g n n ChannelBusyIndicatorn f n n CollisionIndicator

+ =+ =+ =

P P CN N PS S N

⑴

⑵

⑶

⑷

⑸

⑹

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

{ }

[ ] [ ] 1

[ ] [ ] 0

[ ] [ ] [ ] [n],

for any , 1,2, , , for any

MTi i

iTi i

i i j j

n n

n n

n n n

i j M n ConvergenceTime

≤

=

+ = +

∈ ≥

∑S P

S N

S N S N

10/28

Result: ZeroCollision AlgorithmResult: ZeroCollision AlgorithmCSMA/ZCCSMA/ZC

If a station is not transmitting, receiving, and if the medium is detected as idle at least for [DIFS-SLOTTIME], do the followings:— If an idle slot is detected,

Decrement the slot indicator in Neighbor vectorAdvance Pointer vector

— If a busy slot is detected,Update the slot indicator in Neighbor vector

— If inner product of Self vector and Pointer vector is positive,

If tx buffer is not empty, transmit the packet— If a previous tx packet is not acknowledged,

Clear the indicator of Self vector, Choose randomly a vacant slot among the Neighbor vector, and set it to Self vector (#)

— If inner product of Self vector and Neighbor vector is positive,

Do (#)

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

11/28

1

2

3

4

0 0 0 0 0 0 0 00 0 0 0 0 0 0 00 0 0 0 0 0 0 0

0 0 0 0 0 0 0 00 0 0 0 0 0 0 00 0 0 0 0 0 0 0

0 0 0 0 0 0 0 00 0 0 0 0 0 0 00 0 0 0 0 0 0 0

0 0 0 0 0 0 0 00 0 0 0 0 0 0 00 0 0 0 0 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

How to Update N and S: A vanilla exampleHow to Update N and S: A vanilla exampleCW=8, 4 stations, on Simultaneous initialization, Saturated QueuCW=8, 4 stations, on Simultaneous initialization, Saturated Queuee

T0 T1 T2 T3

T4 T5 T6 T10

1

2

3

4

0 0 0 1 0 0 0 00 0 0 0 0 0 0 01 0 0 0 0 0 0 0

0 0 1 0 0 0 0 00 0 0 0 0 0 0 01 0 0 0 0 0 0 0

0 0 0 0 0 0 1 00 0 0 0 0 0 0 01 0 0 0 0 0 0 0

0 0 0 1 0 0 0 00 0 0 0 0 0 0 01 0 0 0 0 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

1

2

3

4

0 0 0 1 0 0 0 00 0 0 0 0 0 0 00 1 0 0 0 0 0 0

0 0 1 0 0 0 0 00 0 0 0 0 0 0 00 1 0 0 0 0 0 0

0 0 0 0 0 0 1 00 0 0 0 0 0 0 00 1 0 0 0 0 0 0

0 0 0 1 0 0 0 00 0 0 0 0 0 0 00 1 0 0 0 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

1

2

3

4

0 0 0 1 0 0 0 00 0 0 0 0 0 0 00 0 1 0 0 0 0 0

0 0 1 0 0 0 0 00 0 0 0 0 0 0 00 0 1 0 0 0 0 0

0 0 0 0 0 0 1 00 0 0 0 0 0 0 00 0 1 0 0 0 0 0

0 0 0 1 0 0 0 00 0 0 0 0 0 0 00 0 1 0 0 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

1

2

3

4

0 0 0 1 0 0 0 00 0 1 0 0 0 0 00 0 0 1 0 0 0 0

0 0 1 0 0 0 0 00 0 0 0 0 0 0 00 0 0 1 0 0 0 0

0 0 0 0 0 0 1 00 0 1 0 0 0 0 00 0 0 1 0 0 0 0

0 0 0 1 0 0 0 00 0 1 0 0 0 0 00 0 0 1 0 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

1

2

3

4

0 1 0 0 0 0 0 00 0 1 1 0 0 0 00 0 0 0 0 1 0 0

0 0 1 0 0 0 0 00 0 0 1 0 0 0 00 0 0 0 0 1 0 0

0 0 0 0 0 0 1 00 0 1 1 0 0 0 00 0 0 0 0 1 0 0

0 0 0 0 0 1 0 00 0 1 1 0 0 0 00 0 0 0 0 1 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

1

2

3

4

0 1 0 0 0 0 0 00 0 1 1 0 0 0 00 0 0 0 1 0 0 0

0 0 1 0 0 0 0 00 0 0 1 0 0 0 00 0 0 0 1 0 0 0

0 0 0 0 0 0 1 00 0 1 1 0 0 0 00 0 0 0 1 0 0 0

0 0 0 0 0 1 0 00 0 1 1 0 0 0 00 0 0 0 1 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

1

2

3

4

0 1 0 0 0 0 0 00 0 1 1 0 1 1 0

0 0 0 0 1 0 0 0

0 0 1 0 0 0 0 00 1 0 1 0 1 1 0

0 0 0 0 1 0 0 0

0 0 0 0 0 0 1 00 1 1 1 0 1 0 0

0 0 0 0 1 0 0 0

0 0 0 0 0 1 0 00 1 1 1 0 0 1 0

0 0 0 0 1 0 0 0

⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦⎡ ⎤⎢ ⎥= ⎢ ⎥⎢ ⎥⎣ ⎦

B

B

B

B

12/28

Expected result of the ZeroCollision MACExpected result of the ZeroCollision MAC

Throughput

Size

100%

79% Theoretical limit

802.11family

Competitors

ZC

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

13/28

Proof of ConceptProof of ConceptBuilding simulators based on ZC algorithmBuilding simulators based on ZC algorithm

ZeroSim: Two Visual MAC Simulators— Perform the same operations— Simulator 1:

1700 lines of Matlab codeScalar processingEmulates each station’s behavior Slow

— Simulator 2:2100 lines of Matlab codeVector processingEmulates a network’s behavior FasterVisualization module is shared with Simulator 1.

Experiment Platform— Intel Pentium4 x 2 nodes— Intel Xeon Cluster computer with 62 nodes

with Dual CPUs

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

14/28

ZeroSim Screenshot ZeroSim Screenshot –– ZC modeZC mode

Base Station

Subscriber Stations

Data Frame

Ack Frame

*Frame lengths are distorted for better visual understanding

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

15/28

ZeroSim Screenshot ZeroSim Screenshot –– 802.11 csma mode802.11 csma mode

*Frame lengths are distorted for better visual understanding

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

16/28

Demo: SimulationDemo: Simulation

17/28

Experiment configurationExperiment configurationTotal 21000 sets of simulation. All are done on the same PHYTotal 21000 sets of simulation. All are done on the same PHY

Saturated queueSaturated queue

Fixed Data frame 200 Bytes

Fixed Data frame 200 Bytes

20 μsec20 μsecSlot time

10 μsec10 μsecSIFS

50 μsec50 μsecDIFS

After 0 no useAfter 5 no useAccess Slot recycle

1 Mbps1 MbpsPLCP overhead Rate

Preamble 18Bytes PLCP header 6 Bytes

Preamble 18Bytes PLCP header 6 BytesPLCP overhead

Ack frame 14 BytesAck frame 14 Bytes

Traffic Model

4, ....,1284, ....,128Network size

32~1024(Dynamic)32 (or 64, 128)Congestion Window

11 Mbps11 MbpsMax Rate

802.11 CSMAZero CollisionMAC

*Most of these parameters are compatible to IEEE 802.11b/HR/DSSS/Long Preamble PHY Specification

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

18/28

Empirical results: Convergence timeEmpirical results: Convergence timeAverage of 100 times simulationAverage of 100 times simulation

ZeroCollision is achieved— After Convergence time, collision is completely free

Immediate convergence— Almost Immediate convergence— Typically less than 150 msec for all users.— Practically convergence time is lesser than this(due to small

association packets)

802.11 CSMA has ∞ convergence time

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

19/28

Empirical results: Channel UtilizationEmpirical results: Channel Utilization= Busytime/Totaltime= Busytime/Totaltime

ZeroCollision MAC > 802.11 CSMA— Theoretical limit is achieved by increasing frame length and

size of network

Is Channel Utilization a good metric ?— No. High collision network may have high utilizatoin

Theoretical limit 97.2%

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

20/28

Empirical results: Goodput ratioEmpirical results: Goodput ratio= Successfully delivered bytes / Trasnmitted bytes= Successfully delivered bytes / Trasnmitted bytes

For Pre-convergence— ZeroCollision MAC < 802.11 CSMA

For Post-convergence— ZeroCollision MAC > 802.11 CSMA

For CSMA— Goodput ratio is strictly decreasing as expected as Network

size grows

Theoretical limit 100%Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

21/28

Empirical results: ThroughputEmpirical results: Throughput= Successfully delivered bytes / Unit time / Max TX Rate= Successfully delivered bytes / Unit time / Max TX Rate

Theoretical limit 79%

For Pre-convergence— ZeroCollision MAC > 802.11 CSMA

For Post-convergence— ZeroCollision MAC > 802.11 CSMA— Theoretical limit is achievable by increasing Frame length and

Size of Network

For 802.11 CSMA— Increasing upto Size of Network = 32*

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

22/28

Features of ZeroCollisionFeatures of ZeroCollision

Guaranteed Upper Delay Bound: Dupper

— 802.11 CSMA, Dupper= ∞— ZC, Dupper= α x Network size

This holds for any kind of traffic modelα = 2.164 msec for 802.11b/HR/DSSS/Longα = 0.839 msec for 802.11a/DSSS-OFDM/LongFor 802.11b, α = Preamble + PLCP header + MAX_MPDU + SIFS + Preamble + PLCP header + MPDUforACK + DIFSFor 802.11a, α = Preamble + PLCP header + OFDM Training sequence + OFDM Signal + MAX_Data + Signal Extension + SIFS + Preamble + PLCP header + OFDM Training sequence + OFDM Signal + ACK + Signal Extension +DIFS

PT=Prob(Throughput Theoretical Limit)*— 802.11 CSMA:PT 0 as Framesize increases— ZC: PT 1 as Framesize increases

Outperforms PCF*— No resource polling/reservation overhead

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

23/28

Application: VoIP PerformanceApplication: VoIP PerformanceCapacity calculation, without silence suppressionCapacity calculation, without silence suppression

Traffic target model— Latency budget=40msec between SS and BS— Voice: G.711. 64Kbps 320 Bytes/40msec— Frame: 394 Bytes/frame— P(Loss)=0

In 802.11b PHY— One source’s portion / 40msec

= Preamble + PLCP header + MPDU + SIFS + Preamble + PLCP header + MPDUforACK + DIFS= 0.741msec

— VoIP Capacity = [40msec / 0.741msec] = 54 sources = 27 sessions

In 802.11a PHY— One source’s portion / 40msec

= Preamble + PLCP header + OFDM Training sequence + OFDM Signal + Data + Signal Extension + SIFS + Preamble + PLCP header + OFDM Training sequence + OFDM Signal + ACK + Signal Extension +DIFS= 0.541 msec

— VoIP Capacity = [40msec / 0.541msec] = 74 sources = 37 sessions

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

24/28

Application: VoIP PerformanceApplication: VoIP Performance802.11 CSMA vs ZeroCollision802.11 CSMA vs ZeroCollision

*N. Hedge, A. Proutiere, and J. Roberts, "Evaluating the voice capacity of 802.11 WLAN under distributed contorl," Proc. LANMAN, 2005

ZeroCollision MAC

400% Improvement •Capacity•Throughput(under the same latency budget)

802.11 CSMA*

25/28

Application: VoIP PerformanceApplication: VoIP PerformanceComparisonComparison

5.3%0.4%

32%8%

Throughput

T. Tung302%Average 20ms54Mbps802.11e

J. Lee560%Average 20ms11MbpsZeroCollision

G.729 8kbps Codec

G.711 64Kbps Codec

J. Lee740%Average 20ms11MbpsZeroCollision

Average 20ms

Latency

14

Capacity

N. HedgeUnknown11Mbps802.11b

ReferenceLoss RateMax Tx RateMAC

26/28

Qualitative Comparison of MACsQualitative Comparison of MACs:: Shopping guide:: Shopping guide

HighHighLowOverhead

★ ★★ ★ ★ ★★ ★ ★Stars

Infinite SoftHardOptionally Dynamic-Hard

HardCapacity

AdaptiveAdaptiveHardConfiguration

Bursty(one packet/period)

Saturated Queue

Bursty(one packet/period)

Saturated Queue

Tmax/MTmaxTmax/M

Approaches to 0TmaxTmaxThroughput

Approaches to UmaxUmaxUmax/M

Umax/CUmaxUmaxChannel Utilization

UnboundedUpper boundedUpper boundedDelay

Shortterm UnfairLongterm Fair

Access FairThroughput FairDelay Fair

Access FairThroughput FairDelay Fair

Fairness

CSMAZeroCollisionTDMAGSM

MAC

Controversial

More ★ ★ ★More Joyful shopping!

27/28

Further ResearchFurther ResearchApplication Area

— Any type of Shared medium accessIncluding the Shared LANBUS architecture of computer system

Bursty node support— Allow Multiple backoff slots for the chatty station

Performance impact of Traffic models— Elastric traffic— Elastric + Realtime traffic

Statistical Learning— Extension to rational numbers— Previous example was a Deterministic Learning

(The station thinks it backoffs with the probability of 1 to avoid the future collisions)

Safeguard against — imperfect carriersensing— Power saving nodes

Dynamic network support— Dynamic CW adjustment

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

28/28

ColclusionColclusionPerformance degradation of 802.11 CSMA

— Collision increases as the network grows

Two principles— Relaxing the infinite soft capacity condition— Learning (from the past)

Crucial Observation— Idle slot as a Sufficient statistic

Proof of Concept: ZeroSim

Performance enhancement— Upper bounded delay— Achievable maximum throughput— 400% capacity/throughput enhancement for VoIP

Comments request

Observation

Initiative Question

Terminology

Principles of ZC

Modeling

Algorithm

Expected Results

Proof of Concept

Empirical results

Features of ZC

VoIP Performance

MAC Comparison

Further Research

Conclusion

29/28

Design Philosophy IDesign Philosophy IFully Distributed Decision

— Every station should be autonomous— No Central Coordination

No predefined schedulingNo Reservation Request – Confirmation based scheduling

Least Memory Size— The memory size used to exploit the transmission

history should be minimized.

Maximize the overall Throughput— The overall throughput of the network should be

relatively increased

Utilization— When chatty stations and shy stations co-exist, the

utilization should not be degraded.Think about TDM case. Let’s avoid it.

Fairness— When plural chatty stations exist, the equillribrium

point of the share should be unique. — The share of greedy stations should meet at the unique

equilllibrium point with the fair shares

30/28

Design Philosophy IIDesign Philosophy IIComputational Complexity

— Computational complexity required at each station should be O(n1)

— Suboptimality of the solution is welcome.

Backward Compatibility— The algorithm should be modular enough— The algorithm should be highly compatible to the well-

known wireless LAN technologies – such as IEEE 802.11This means the possibility of co-existence of Exponential Backoff algorithm and Zero Collision Backoff algorithm

Generality— The algorithm should be easily applied to other kinds of

random access networks.

Support of Power Saving stations— They should not be ruled out of the benefit of the

algorithm

Support of Non-stationary network— The algorithm should be flexible enough to

accommodate a highly non-stationary network.