6 november 2002 mac protocol 1 optimization of the efficiency of mac protocols for wlans raffaele...

MAC protocol 1 6 November 2002

Optimization of the Efficiency of MAC

Protocols for WLANs

Raffaele Bruno

MobileMAN

kickoff meeting


Outline

MAC protocols for WLANs: the IEEE 802.11 solution

Inefficiencies of the IEEE 802.11 MAC protocol

Definition of the optimal backoff scheme to maximize the resource utilization

Performance evaluation

Conclusions


Why the MAC protocol is important?

The wireless medium is an intrinsic shared medium

The channel access becomes a fundamental factor in determining the capacity of the network and has a great impact on system complexity and/or cost

The contention MAC protocols, or random access protocols, use a direct contention to determine channel access rights. Needs for collisions avoidance and collision resolution mechanisms:

randomization of retransmissions

mechanisms for channel reservation

fairness in the randomization of access


Power Consumption

The finite battery power of portable devices represents a severe limitation to the utility of WLANs. The data transmission and reception are one of the most power-consuming activities that these devices have to perform

About the 20% of the battery life is determined by the network interface. For the handheld devices the impact of the network interface can be up to the 50%

11520 10200 1320Time (seconds)

3 h 12 m

2 h 50 m

22 m

WaveLAN ON

WaveLAN OFF

WaveLAN Card Consumtpion


The IEEE 802.11 Protocol Stack

Each node executes locally and independently from the other nodes a Coordination Function that defines the mechanisms for sharing the bandwidth.

This technology defines a Distributed Coordination Function (DCF) for the delivery of asynchronous traffic, and a Point Coordination Function (PCF) for the delivery of synchronous traffic

Point Coordination Function

Distributed Coordination Function

Physical Layer

MAC sublayer

contention freeservices contention

services

FundamentalAccess Method


The Distibuted Coordination Function

The Distributed Coordination Function adopts the Carrier Sensing Multiple Access (CSMA) scheme: a station is allowed to transmit only when it senses no other transmissions on the channel

The CSMA is both “physical” and “virtual”: physical carrier sensing: the receiver assumes the channel

busy when a radio signal power above the sensitivity threshold is detected on the air

virtual carrier sensing: the channel is considered busy for all the expected remaining time required to complete the actual exchange of data


DCF Basic Access: overview Successful transmission

Collision

DATA

ACK

NAVCW

DIFS

DIFS

SIFSSource

Destination

Other

There is no collision detection: each collided packet is completely transmitted

LA

Collision Length = collided packet maximum length (LA)

DIFS EIFSSource A

Source B

Source C

LB

LC

COLLISION LENGTH


DCF RTS/CTS Access: overview Successful transmission

Collision

Collision Length = length (RTS)

Trade-off between the increased control overheads and the reduced collision costs

RTSADIFSSource A

Source B

Source C

RTSB

RTSC

COLLISION LENGTH

EIFS

Source

Destination

Other

DATA

ACK

NAV RTSCW

DIFS

DIFS

SIFS

RTS

SIFS

SIFS

CTS

NAV CTS

NAV Data


Collision Avoidance & Resolution scheme Collision Avoidance scheme to reduce the probability to

collide before transmitting a new packet: it is not enough to listen the channel idle to transmit, the station set

a random “backoff counter” to defer the transmission

Collision Resolution scheme to reduce the probability to collide again on the retransmissions of the same packet:

the “backoff counter” is increased after each retransmission of the same packet

The “backoff counter” is selected through the Binary Exponential Backoff (BEB)


The BEB algorithm

The backof timer is uniformly sampled within the range [0…CW-1], where CW is the Contention Window

The Contention Window is doubled after each consecutive retransmission of the same packet

The Contention Window shall be reset to a CWmin value after each successful transmission

3163

127

255

511

1023

# of transmissions

1 2 3 4 5 6 7

CWmax

CWmin


The BEB inefficiencies

The BEB procedure implemented is reactive and not proactive: it is triggered by a collision event, hence it does not try to predict collisions

The status information exploited by the BEB is very limited, only the number of consecutive collisions. Other feedback information as the collisions’ length can be utilized?

The BEB algorithm is known to have unpredictable fairness properties in the presence of heavy contention, since it tends to favor the station that experienced the last successful transmission


Increasing the MAC efficiency

A good indication of the bandwidth efficiency is the protocol capacity, i.e., the maximum channel utilization achievable by the MAC protocol, whereas the minimum energy consumption is a good indication of the energy efficiency

Through a model of the MAC protocol operation it is feasible to derive the optimal protocol operating state that guarantees the optimal performances

CHANNEL UTILIZATION ( ) = fraction of channel bandwidth used

by successfully transmitted messages

€

ρ

ENERGY CONSUMTPION = energy used by the network interface

to successfully transmit a message


How to model MAC protocols?

The asymptotic behavior of the IEEE 802.11 MAC protocol can be modeled via a p-persistent MAC protocol , where each station decides to transmit at the beginning of an empty slot according to a probability of transmission p *

1-p

begin of anempty slot

p the station transmits in the slot

the station waits next empty slot

*F. Calì, M. Conti, E. Gregori, "Dynamic Tuning of the IEEE 802.11Protocol to Achieve a

Theoretical Throughput Limit", IEEE/ACM Transactions on Networking, December 2000


Protocol Capacity analysis

end of j-th transmission

attempt

end of (j+1)-th transmission

attempt

Idle Period Collision/Success

Protocol Capacity :

€

ρMAX =maxp∈ 0,1[ ]

ρ =l ⋅ tslot⋅ Psucc|N tr ≥1

E tv[ ]

⎧ ⎨ ⎪

⎩ ⎪

⎫ ⎬ ⎪

⎭ ⎪

€

E tv[ ]=E Idle_ p[ ]+l ⋅tslot⋅ PSucc|Ntr ≥1 +E Coll|Collision[ ] ⋅Pcoll|Ntr ≥1

The closed formulas can be derived for a general packet length distribution, by assuming:

a finite network population with M stations a heavily loaded network


Energy Consumption analysis

NOTE: PTX > PRX

Tagged Success

Tagged Collision

Not-Tagged Success/Collision

virtual transmission time

From the energy consumption standpoint, the network interface alternates between transmitting phases, where it consumes PTX power per second, and receiving phases, where it consumes PRX power per second

Energy Efficiency :

€

ρenergy=PTX ⋅ l ⋅ tslot

E Energyvirtual_ transmission_ time[ ]


Capacity vs. Energy Consumption analysis

In a network with M stations, when PTX=PRX, it holds that:

€

ρenergy=ρM

To attain either the Protocol Capacity or the Minimum Energy Consumption are

orthogonal goals?

The Protocol Capacity analysis is a special case of the more general mathematical framework of the Energy Consumption analysis


The Mpopt product

l = 2 time slots l = 100 time slots

0

0.2

0.4

0.6

0.8

1Mpopt

0 20 40 60 80 100M

PTX/PRX=10

PTX/PRX=2

PTX/PRX=1

0

0.05

0.1

0.15

0.2Mpopt

0 20 40 60 80 100M

PTX/PRX=10

PTX/PRX=2

PTX/PRX=1

The average number of transmitting station (Mp product) that guarantees the optimal energy state (optimal capacity state) is almost independent of the M value, at least for PTX/PRX<2


An approximate formula for the popt value

REMARK

€

popt M >>1,C >>1 ⏐ → ⏐ ⏐ ⏐ 1

M ⋅ 2C

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1Mpopt

0 20 40 60 80 100M

PTX/PRX=10PTX/PRX=2

PTX/PRX=1approximation

l=2

l=100

The derived closed formula cannot be used to tune the tune the protocol to the optimal state because it is necessary to know the number of contending stations in the network. This information is difficult to be retrieved in a mobile environment


Dynamic Tuning of the MAC protocol

Each station at runtime must computes the popt value by observing the status of

the channel

popt = f(M,l,PTX,PRX)

Any feedback-based strategy to achieve Power-Saving/Efficiency Optimization should be

EFFECTIVE

To be based only on simple channel status estimates, without the need of information

about the number of active stations

To require negligible computational complexity

To approach as much as possible the theoretical bounds

SIMPLE

EASY


Approximated analysis

To minimize the Energy Consumption we must minimize only the terms depending on the p value:

€

minp

E Nta[ ] ⋅ E EnergyIdle_ p[ ]+ E Nta[ ]−M( )⋅ E EnergyColl |Coll[ ]{{ }

€

E EnergyIdle_ p[ ]=E EnergyColl |Ntr ≥1[ ]


Tagged Success1 Not-Tagged SuccessM-1

CollisionsE[Nta]-M Idle PeriodsE[Nta]


Approximation validation

The E[EnergyIdle_p] is a degreasing function of the p value, whereas the E[EnergyColl] is an increasing function of the p value

The Optimal State is the balance between these two conflicting costs

0.01

0.1

1

10

100Energy

0 0.02 0.04 0.06 0.08 0.1p

E[Energy Coll ] - PTX/PRX=10



E[Energy Idle_p ]


Dinamic Tuning strategy: overview stations that adopt a p value > popt have a too much aggressive behavior

stations that adopt a p value < popt have a too much conservative behavior


Collisions Idle Periods

• p < popt

• p = popt

• p > popt

€

E EnergyIdle_ p[ ]>E EnergyColl |Ntr ≥1[ ]

€

E EnergyIdle_ p[ ]=E EnergyColl |Ntr ≥1[ ]

€

E EnergyIdle_ p[ ]<E EnergyColl |Ntr ≥1[ ]


Dinamic Tuning strategy: implementation

n-th idle period n-th transmission

end of (n-1)-th transmission attempt

updating point n-1

end of n-th transmission attempt

updating point n

€

E EnergyIdle_ p[ ]n

€

€

E Energynot_ tag_ Coll |Ntr ≥1[ ]n

€

E Energytag_Coll |Ntr ≥1[ ]n

updating

updating

€

E EnergyIdle_ p[ ]n

€

E EnergyIdle_ p[ ]n−1

€

E EnergyColl |Ntr ≥1[ ]n

€

E EnergyColl |Ntr ≥1[ ]n−1

€

pn

€

pn+1

€

E Idle_ p[ ]n =α ⋅ E Idle_ p[ ]n−1 + 1−α( ) ⋅ Idle_ pn

€

E Energytag_Coll |Ntr ≥1[ ]n=α ⋅ E Energytag_Coll |Ntr ≥1[ ]

n−1+ 1−α( )⋅ PTX ⋅Coll_ taggedn +[

PRX⋅max0,Colln −Coll_ taggedn( )]

€

E Energynot_ tag_ Coll |Ntr ≥1[ ]n=α ⋅ E Energynot_ tag_Coll |Ntr ≥1[ ]n−1

+ 1−α( )⋅ PRX⋅Coll_ not_ taggedn


Dinamic Tuning strategy: implementation

At the end of (n-1)-th transmission attempt, the transmission control strategy calculates a new p value, say pnew, as a function of previous adopted p value

By exploiting the same approximation adopted to derive the popt closed formulas, we obtain

pnew = pn(1+x)

€

pnew=pn ⋅

1+41+E Idle_ p[ ]n( )⋅E Energytag_Coll |Ntr ≥1[ ]n

+E Energynot_ tag_ Coll |Ntr ≥1[ ]n

PRX

⎛

⎝ ⎜ ⎜

⎞

⎠ ⎟ ⎟ −1

2⋅E Energytag_Coll |Ntr ≥1[ ]n

+E Energynot_ tag_ Coll |Ntr ≥1[ ]n

PRX

⎛

⎝ ⎜ ⎜

⎞

⎠ ⎟ ⎟


Power Saving-Efficient IEEE 802.11 protocol The Power Saving (PS)-Efficient IEEE 802.11 protocol is a p-persistent IEEE

802.11 protocol where the p value is dynamically computed according to the transmission control strategy previously described

The numerical analysis performed takes in consideration all the physical and MAC overheads

success_overhead = 2+SIFS+ACK+DIFS

collision_overhead = +EIFS

MAC_HDR

PHY_HDR FCS

DATA

tslot PHY_hdr MAC_hdr FCS Bit Rate

50 se c 50 se 128 bits(2.56 tslot)

2 Mbps

DIFS SIFS EIFS ACK CWmin CWmax364 sec (7.24 tslot)

112 bits + PHY_hdr 8 tslot 256 tslot

1 sec 240 bits(2.4 tslot)

32 bits(0.32 tslot)

28 sec (0.56 tslot)

128 sec (2.56 tslot)


PS-Efficient 802.11: steady state analysis

100

1000

Energy Consumption

0 10 20 30 40 50 60 70 80 90 100M

PS-E 802.11 (alfa=0.99)

STD 802.11

OPT 802.11

100

1000

Energy Consumption

0 10 20 30 40 50 60 70 80 90 100M

PS-E 802.11 (alfa=0.99)

STD 802.11

OPT 802.11

PS-Efficient IEEE 802.11 approaches theoretical lower bound for the Energy Consumption in every network configurations and traffic

characteristics analyzed

l=2,PTX/PRX=2 l=2,PTX/PRX=10


PS-Efficient 802.11: transient analysis

100

1000

10000

Energy Consumption

20 40 60 80 100 120 140

Time (2048 time slots)

OPT 802.11

STD 802.11

PS-E 802.11 (alfa=0.99)

(M=10)201.11

(M=100)2015.50

200

400

600

800

1000

1200

1400

1600

1800Energy Consumption

20 40 60 80 100 120 140

Time (2048 time slots)

OPT 802.11

STD 802.11

PS-E 802.11 (alfa=0.99)

PS-Efficient IEEE 802.11 reaches promptly a new optimal stationary state after both sharp and frequent variation of the number of active stations

l=2,PTX/PRX=2 l=2,PTX/PRX=2


PS-Efficient 802.11: MAC delay analysis

PS-Efficient IEEE 802.11 significantly improves both average and worst-case MAC Delay

M=10, l=2, PTX/PRX=2

Averagevalue

99thpercentile

99.9thpercentile

M=10, l=100, PTX/PRX=2

Averagevalue

99thpercentile

99.9thpercentile


Conclusions & Future work

Conclusions:

– With the current technology of network interfaces (PTX/PRX<2) the Energy Consumption Minimization and the Channel Utilization Maximization can be jointly achieved

– The energy and bandwidth Efficiency in IEEE 802.11 networks can be significantly improved by modifying the backoff procedure

– The intrinsic characteristics of p-persistent CSMA protocols allow us to define adaptive feedback-based backoff-tuning policies that are completely distributed and independent of the network population

Future Work:

– Extension to the multi-hop case

– Introduction of traffic priotization

6 november 2002 mac protocol 1 optimization of the efficiency of mac protocols for wlans raffaele...

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