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IEEE 802.11 Wireless LAN:IEEE 802.11 Wireless LAN:Capacity Analysis Capacity Analysis
and Protocol Enhancementand Protocol Enhancement
F. Cali, M. Conti, E. GregoriF. Cali, M. Conti, E. Gregori
IEEE 802.11 Wireless LAN:IEEE 802.11 Wireless LAN:Capacity Analysis Capacity Analysis
and Protocol Enhancementand Protocol Enhancement
F. Cali, M. Conti, E. GregoriF. Cali, M. Conti, E. Gregori
Vangelis AngelakisVangelis Angelakis23 / 3 / 200523 / 3 / 2005
CS-539: Mobile Networks & ComputingCS-539: Mobile Networks & ComputingCS-539: Mobile Networks & ComputingCS-539: Mobile Networks & Computing
IntroductionIntroduction
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Federico Cali, Marco Conti and Enrico Gregori
"IEEE 802.11 Wireless LAN: Capacity Analysis and Protocol Enhancement"
Proceedings of the Conference on Computer CommunicationsIEEE Infocom’98San Francisco, California, USA. March/April 1998.available online at: http://www.ieee-infocom.org/1998/papers/02a_2.pdf
Institute for Informatics & Telematics (IIT), National Research Council (CNR), IT.
Federico Cali, Marco Conti and Enrico Gregori
"IEEE 802.11 Wireless LAN: Capacity Analysis and Protocol Enhancement"
Proceedings of the Conference on Computer CommunicationsIEEE Infocom’98San Francisco, California, USA. March/April 1998.available online at: http://www.ieee-infocom.org/1998/papers/02a_2.pdf
Institute for Informatics & Telematics (IIT), National Research Council (CNR), IT.
IntroductionIntroduction
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Communication in the 802.11 relies on a shared transmission medium.
The 802.11 MAC layer coordinates the transmissions of the n/w STAs
Transmission control information in the 802.11 MAC is both explicit and implicit.
Explicit: Control Messages (ACK, RTS, CTS…)
Implicit: Timing (SIFS, DIFS…) and Channel Condition (BUSY / IDLE –channel
sensing )
Communication in the 802.11 relies on a shared transmission medium.
The 802.11 MAC layer coordinates the transmissions of the n/w STAs
Transmission control information in the 802.11 MAC is both explicit and implicit.
Explicit: Control Messages (ACK, RTS, CTS…)
Implicit: Timing (SIFS, DIFS…) and Channel Condition (BUSY / IDLE –channel
sensing )
IntroductionIntroduction
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Control messages and message retransmissions reduce bandwidth available for successful message transmissions.
The bandwidth fraction used for successfully transmitted messages gives a good indication of the overhead the MAC layer requires to perform its coordination task.
Control messages and message retransmissions reduce bandwidth available for successful message transmissions.
The bandwidth fraction used for successfully transmitted messages gives a good indication of the overhead the MAC layer requires to perform its coordination task.
IntroductionIntroduction
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Control messages and message retransmissions reduce bandwidth available for successful message transmissions.
The bandwidth fraction used for successfully transmitted messages gives a good indication of the overhead the MAC layer requires to perform its coordination task.
This is called Utilization and is usually influenced by several parameters. The paper focuses on:
i) the number of active n/w STAs, andii) the way they contribute to the offered load
The maximum value of the Utilization is the MAC protocol Capacity
Control messages and message retransmissions reduce bandwidth available for successful message transmissions.
The bandwidth fraction used for successfully transmitted messages gives a good indication of the overhead the MAC layer requires to perform its coordination task.
This is called Utilization and is usually influenced by several parameters. The paper focuses on:
i) the number of active n/w STAs, andii) the way they contribute to the offered load
The maximum value of the Utilization is the MAC protocol Capacity
The 802.11 Medium Access ControlThe 802.11 Medium Access Control
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
The basic access method in 802.11 MAC is the Distributed Coordination Function (DCF).
The 802.11 DCF is a Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) MAC protocol.
The basic access method in 802.11 MAC is the Distributed Coordination Function (DCF).
The 802.11 DCF is a Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) MAC protocol.
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
I have a packet to send to B, must sense the
medium to avoid collissions
I have a packet to send to B, must sense the
medium to avoid collissions
t
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
Time passes…
t
DIFS
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
Channel idle for DIFS
I am starting transmission to B.
Channel idle for DIFS
I am starting transmission to B.
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
τ
DIFS
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ
I have a packet to send…
Sensed medium to be BUSY
defering until IDLE
I have a packet to send…
Sensed medium to be BUSY
defering until IDLE
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ
deferring
Must Acknowledge
packet reception
Must Acknowledge
packet reception
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τMedium is IDLE, lets see if
it remains idle for DIFSMedium is IDLE, lets see if
it remains idle for DIFS
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ
Time passes…
SIFS
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ SIFS
deferring
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ SIFS
Medium is IDLE, lets see if it remains idle for DIFS
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ
Time passes…
SIFS
DIFS
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ
Time passes…
SIFS
DIFS
Backing off
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ SIFS
DIFS
Contention
Window
802.11 DCF802.11 DCF
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
AA
BB
CC
t
DIFS
τ SIFS
DIFS
Time slot = time required to sense the medium
Backoff handlingBackoff handling
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
The # of slots (backoff interval) is uniformly selected in the (0, CWi ) interval
With each idly passing slot the backoff timer is reduced
If during the backoff interval the channel becomes busy then the timer is paused and is reactivated next time the channel is idle for DIFS
If this leads to a collision, then the station will have to retransmit, this time selecting the backoff interval in the (0, 2 xCWi ) interval
The initial CW is CWmin and a CWmax is also defined.
The # of slots (backoff interval) is uniformly selected in the (0, CWi ) interval
With each idly passing slot the backoff timer is reduced
If during the backoff interval the channel becomes busy then the timer is paused and is reactivated next time the channel is idle for DIFS
If this leads to a collision, then the station will have to retransmit, this time selecting the backoff interval in the (0, 2 xCWi ) interval
The initial CW is CWmin and a CWmax is also defined.
RTS/CTSRTS/CTS
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
The Request-To-Send / Clear-To-Send message exchange is optional.
Used to avoid the hidden terminal problem.
After gaining channel control and before the actual data packet transmission the sender sends a unicast RTS frame.
This is answered by a broadcast CTS from the receiving STA.
-The RTS/CTS mechanism is accounted for in this work.
The Request-To-Send / Clear-To-Send message exchange is optional.
Used to avoid the hidden terminal problem.
After gaining channel control and before the actual data packet transmission the sender sends a unicast RTS frame.
This is answered by a broadcast CTS from the receiving STA.
-The RTS/CTS mechanism is accounted for in this work.
Capacity analysis: Definitions & Notations
Capacity analysis: Definitions & Notations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
ρmax the capacity in asymptotic conditions of M active
stations
ρsingle the capacity considering a single active station
asymptotic conditions (a.c.): All stations have a packet ready to transmit
ideally: ρsingle = ρ max = 1
The paper estimates capacity by evaluating in a.c. the ratio:_
Where: m average message length and
tv virtual transmission time : the average time
the channel is occpied in transmitting a message
ρmax the capacity in asymptotic conditions of M active
stations
ρsingle the capacity considering a single active station
asymptotic conditions (a.c.): All stations have a packet ready to transmit
ideally: ρsingle = ρ max = 1
The paper estimates capacity by evaluating in a.c. the ratio:_
Where: m average message length and
tv virtual transmission time : the average time
the channel is occpied in transmitting a message
vt
m
vt
m
Capacity analysis: One active stationCapacity analysis: One active station
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Let S denote the time required for a successful transmission.
Then assuming that the average backoff time is E [ CW ] it follows that:
tv = E [ S ] + E [ CW ]
We consider a single active station, no collisions =>
CW always from the (0, CWmin) interval => E [ CW ] = CWmin/2
LEMMA #1:
Let S denote the time required for a successful transmission.
Then assuming that the average backoff time is E [ CW ] it follows that:
tv = E [ S ] + E [ CW ]
We consider a single active station, no collisions =>
CW always from the (0, CWmin) interval => E [ CW ] = CWmin/2
LEMMA #1:
(1)
(2)
DIFSACKSIFSmS 2 DIFSACKSIFSmS 2
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
m
Time: t0Time: t0
m
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
Time: t0 + mTime: t0 + m
m
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
Time: t0 + m + τab Time: t0 + m + τab
ACK
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
Time: t0 + m + τab + SIFS Time: t0 + m + τab + SIFS
ACK
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
Time: t0 + m + τab + SIFS + τbaTime: t0 + m + τab + SIFS + τba
ACK
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
Time: t0 + m + τab + SIFS + τba + ACKTime: t0 + m + τab + SIFS + τba + ACK
A short proof that A short proof that
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
DIFSACKSIFSmS 2
AA BB
Time: t0 + m + τab + SIFS + τba + ACK + DIFSTime: t0 + m + τab + SIFS + τba + ACK + DIFS
Capacity analysis: One active stationCapacity analysis: One active station
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
yields that E[S] = m + 2τ + SIFS + ACK + DIFS
With (1), (2) & (3) it follows that
Assuming packet lengths to be: - integer multiples of the slot length tslot
- i.i.d. geometrically distributed with parameter q then
yields that E[S] = m + 2τ + SIFS + ACK + DIFS
With (1), (2) & (3) it follows that
Assuming packet lengths to be: - integer multiples of the slot length tslot
- i.i.d. geometrically distributed with parameter q then
DIFSACKSIFSmS 2 DIFSACKSIFSmS 2
_ (3)
( 2 ) (CWmin/2)Single
m
m SIFS ACK DIFS
( 2 ) (CWmin/2)Single
m
m SIFS ACK DIFS
)1( q
tm slot
)1( q
tm slot
Capacity analysis: More active stationsCapacity analysis: More active stations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
In this case the virtual transmission time tv must include, not
only the successful transmission, but also:-the collision intervals -the DIFS’ after each collision event-the propagation time τ-the idle periods due to the backoff algorithm
In this case the virtual transmission time tv must include, not
only the successful transmission, but also:-the collision intervals -the DIFS’ after each collision event-the propagation time τ-the idle periods due to the backoff algorithm
Coll1Coll1 DIFSDIFS ColliColli DIFSDIFS SS…
tv tv
Idle_ pi Idle_ pi
Collision Collision Successfultransmission
Successfultransmission
i i 1 1 Ν+1Ν+1
Capacity analysis: More active stationsCapacity analysis: More active stations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
From the previous slide we have:
In 802.11 duration of a collision equals the maximum length of the colliding packets.So, the collision duration (Colli ) depends on:
- the packet size distribution- the backoff algorithm (number of colliding
stations)The length of idle periods (Idle_pi ) depends on
- the backoff algorithm
From the previous slide we have:
In 802.11 duration of a collision equals the maximum length of the colliding packets.So, the collision duration (Colli ) depends on:
- the packet size distribution- the backoff algorithm (number of colliding
stations)The length of idle periods (Idle_pi ) depends on
- the backoff algorithm
SEpIdleEDIFSCollpIdleEt N
N
iiiv
1
1
__ SEpIdleEDIFSCollpIdleEt N
N
iiiv
1
1
__
…
Capacity analysis: More active stationsCapacity analysis: More active stations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
To compute the two unknowns by taking the 802.11 backoff algorithm is impossible due to introduced interdependencies.
Instead, the authors denote I to be the number of attempts to successfully transmit a packet.
So each station experiences I backoff times {B1, B2, …, BI },
sampled uniformly in intervals of length {CW1, CW2,…,CWI}
To compute the two unknowns by taking the 802.11 backoff algorithm is impossible due to introduced interdependencies.
Instead, the authors denote I to be the number of attempts to successfully transmit a packet.
So each station experiences I backoff times {B1, B2, …, BI },
sampled uniformly in intervals of length {CW1, CW2,…,CWI}
Capacity analysis: More active stationsCapacity analysis: More active stations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
To simplify the analysis authors assume that stations for each transmission attempt use a backoff interval sampled from a geometric distribution with parameter p, where p = 1 / ( E [B ] + 1 ), with E [B ] being the average value of {B1, B2, …, BI }, expressed in number
of slots.
LEMMA #2: E [B ] = (E [CW ] – 1) / 2Where E [CW ] is the average contention window in number of slots.
The above assumption on the backoff algorithm implies that future behaviour does not depend on the past.
To simplify the analysis authors assume that stations for each transmission attempt use a backoff interval sampled from a geometric distribution with parameter p, where p = 1 / ( E [B ] + 1 ), with E [B ] being the average value of {B1, B2, …, BI }, expressed in number
of slots.
LEMMA #2: E [B ] = (E [CW ] – 1) / 2Where E [CW ] is the average contention window in number of slots.
The above assumption on the backoff algorithm implies that future behaviour does not depend on the past.
Capacity analysis: More active stationsCapacity analysis: More active stations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
So in a virtual transmission the following assumptions can be made
(especially under a large number of stations M ):
i) The idle periods duration Idle_pi are i.i.d. sampled from
a geometric distribution with average E [ Idle_p ]
ii) The collision duration Colli are i.i.d. with average E
[Coll ]
So equation:
Can become:
So in a virtual transmission the following assumptions can be made
(especially under a large number of stations M ):
i) The idle periods duration Idle_pi are i.i.d. sampled from
a geometric distribution with average E [ Idle_p ]
ii) The collision duration Colli are i.i.d. with average E
[Coll ]
So equation:
Can become:
SEpIdleEDIFSCollpIdleEt N
N
iiiv
1
1
__ SEpIdleEDIFSCollpIdleEt N
N
iiiv
1
1
__
SENEpIdleEDIFSCollENEtv 1_ SENEpIdleEDIFSCollENEtv 1_
Capacity analysis: More active stationsCapacity analysis: More active stations
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Shortly we will see how E [CW ] can be calculated and p derived from it
Assuming it known, tv depends on E [N ], E [Idle_p ] and E
[Coll ]
LEMMA #3: If the backoff interval for each station is sampled for a geometric distribution with parameter p then:
Shortly we will see how E [CW ] can be calculated and p derived from it
Assuming it known, tv depends on E [N ], E [Idle_p ] and E
[Coll ]
LEMMA #3: If the backoff interval for each station is sampled for a geometric distribution with parameter p then:
SENEpIdleEDIFSCollENEtv 1_ SENEpIdleEDIFSCollENEtv 1_
1)1(
)1(11
M
M
ppM
pNE 1
)1(
)1(11
M
M
ppM
pNE slotM
M
tp
ppIdleE
)1(1
)1(_
slotM
M
tp
ppIdleE
)1(1
)1(_
1
11
1 1
)1()1()1(
])1()1[(1][
h
MMhMh
MMslot
q
pMppqpqh
pMpp
tCollE
1
11
1 1
)1()1()1(
])1()1[(1][
h
MMhMh
MMslot
q
pMppqpqh
pMpp
tCollE
Capacity analysis: Estimating E [CW ]Capacity analysis: Estimating E [CW ]
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Lets focus on a tagged station and compute E [CW ] as the limiting value of the sequence {E [CW ( n ) ], n=1,2,…}.
The first value of the sequence E [CW ( 0 )] is the average minimum CW and
E [CW ( i+1 )] = Ψ (E [CW ( i )])
Specifically E [CW ( i+1 )] is the tagged station’s i-th average contention window computed under the assumption that all stations in the network transmit with probability p (i ) = 2 / (E [CW ( i )]+1)
Lets focus on a tagged station and compute E [CW ] as the limiting value of the sequence {E [CW ( n ) ], n=1,2,…}.
The first value of the sequence E [CW ( 0 )] is the average minimum CW and
E [CW ( i+1 )] = Ψ (E [CW ( i )])
Specifically E [CW ( i+1 )] is the tagged station’s i-th average contention window computed under the assumption that all stations in the network transmit with probability p (i ) = 2 / (E [CW ( i )]+1)
Capacity analysis: Estimating Ψ (E [CW ( i )])Capacity analysis: Estimating Ψ (E [CW ( i )])
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
When the tagged station transmits it will experience a collision if another station also attempts to transmit.
The probability of a collision at the (i+1)-th attempt is pcoll
(i+1) = 1 – (1-p (i ))M-1
It follows that the tagged station will experience h collisions before successfully transmitting a packet with probabilty:
P{Ncoll(i+1)=h } = ( pcoll
(i) )h . (1 - pcoll (i) )
Where Ncoll(i+1) is the number of collisions experienced by the
tagged station at the (i+1)-th iteration
When the tagged station transmits it will experience a collision if another station also attempts to transmit.
The probability of a collision at the (i+1)-th attempt is pcoll
(i+1) = 1 – (1-p (i ))M-1
It follows that the tagged station will experience h collisions before successfully transmitting a packet with probabilty:
P{Ncoll(i+1)=h } = ( pcoll
(i) )h . (1 - pcoll (i) )
Where Ncoll(i+1) is the number of collisions experienced by the
tagged station at the (i+1)-th iteration
Capacity analysis: Estimating Ψ (E [CW ( i )])Capacity analysis: Estimating Ψ (E [CW ( i )])
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Experiencing h collisions means that the station will use h+1 contention windows which will be selected according to the 802.11 backoff algorithm.
Experiencing h collisions means that the station will use h+1 contention windows which will be selected according to the 802.11 backoff algorithm.
Capacity analysis: Estimating Ψ (E [CW ( i )])Capacity analysis: Estimating Ψ (E [CW ( i )])
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Lemma #4: Denoting Eh the set of contention windows used
by the tagged station when it experiences h collisions before a successful transmission then:
Where:
and
is given in the table which is constructed considering the behaviour of the backoff algorithm
Lemma #4: Denoting Eh the set of contention windows used
by the tagged station when it experiences h collisions before a successful transmission then:
Where:
and
is given in the table which is constructed considering the behaviour of the backoff algorithm
0
)1()1()1()1(
hh
ih
iii ECWPECWxCWPxCWP
0
)1()1()1()1(
hh
ih
iii ECWPECWxCWPxCWP
1
)1()1(
)1()1(
icoll
icoll
hi
NE
hNPhECWP
1
)1()1(
)1()1(
icoll
icoll
hi
NE
hNPhECWP
hii ECWxCWP )1()1( hii ECWxCWP )1()1(
Simulation verificationSimulation verification
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
The simulation confidence interval (confidence 90%) contains the analytically derived estimate
Packets were assumed to have a geometric distribution with q=0.99.
The simulation confidence interval (confidence 90%) contains the analytically derived estimate
Packets were assumed to have a geometric distribution with q=0.99.
BacktrackingBacktracking
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
We had the following:
We assume q, but needed p.
We had p (i ) = 2 / (E [CW ( i )]+1) And just showed the algorithm for E [CW ( i )] calculation.
We had the following:
We assume q, but needed p.
We had p (i ) = 2 / (E [CW ( i )]+1) And just showed the algorithm for E [CW ( i )] calculation.
SENEpIdleEDIFSCollENEtv 1_ SENEpIdleEDIFSCollENEtv 1_
1)1(
)1(11
M
M
ppM
pNE 1
)1(
)1(11
M
M
ppM
pNE slotM
M
tp
ppIdleE
)1(1
)1(_
slotM
M
tp
ppIdleE
)1(1
)1(_
1
11
1 1
)1()1()1(
])1()1[(1][
h
MMhMh
MMslot
q
pMppqpqh
pMpp
tCollE
1
11
1 1
)1()1()1(
])1()1[(1][
h
MMhMh
MMslot
q
pMppqpqh
pMpp
tCollE
The CapacityThe Capacity
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Capacity BoundsCapacity Bounds
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
For a given packet length, capacity is maximized when the average virtual transmission time is minimized.As we have seen tv is a function of M, p and q.
Authors fix the values of q and M and try to derive the minimum of the tv( p ) function.
For a given packet length, capacity is maximized when the average virtual transmission time is minimized.As we have seen tv is a function of M, p and q.
Authors fix the values of q and M and try to derive the minimum of the tv( p ) function.
Capacity BoundsCapacity Bounds
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Low p values yield high tv
values due to high number of empty slots before a transmission(low probability of collision)
Low p values yield high tv
values due to high number of empty slots before a transmission(low probability of collision)High p values imply a high number of collisions before a successful transmission.
Bottom line:The minimum tv can be derived for each q and from that
the analytical upper bound of the MAC capacity.
High p values imply a high number of collisions before a successful transmission.
Bottom line:The minimum tv can be derived for each q and from that
the analytical upper bound of the MAC capacity.
Capacity BoundsCapacity Bounds
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Improving the IEEE 802.11 MAC capacityImproving the IEEE 802.11 MAC capacity
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
The critical point for the distance between the analytical capacity bound and the simulated results is the average backoff time which determines the probability of a collision: p (i ) = 2 / (E [CW ( i )]+1)
The critical point for the distance between the analytical capacity bound and the simulated results is the average backoff time which determines the probability of a collision: p (i ) = 2 / (E [CW ( i )]+1)
To demonstrate the figure compares the analytical bound to a simulation of an 802.11 network with a constant contention window sized equal to the optimal value 2/pmin-1
with the value of pmin taken
from the table in the previous slide.
To demonstrate the figure compares the analytical bound to a simulation of an 802.11 network with a constant contention window sized equal to the optimal value 2/pmin-1
with the value of pmin taken
from the table in the previous slide.
Improving the IEEE 802.11 MAC capacityImproving the IEEE 802.11 MAC capacity
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Goal: to reach the analytically estimated capacity bound
Method: modify the 802.11 backoff algorithm,
providing it with an optimal constant CW.Bummer:
optimal CW is derived from the pmin and
the pmin value depends also on M and q.
i.e.: the optimal CW size depends on the network load…
To reach the maximum capacity the contention window must be computed in real-time estimating the M and q values…
Goal: to reach the analytically estimated capacity bound
Method: modify the 802.11 backoff algorithm,
providing it with an optimal constant CW.Bummer:
optimal CW is derived from the pmin and
the pmin value depends also on M and q.
i.e.: the optimal CW size depends on the network load…
To reach the maximum capacity the contention window must be computed in real-time estimating the M and q values…
Capacity with known M Capacity with known M
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
In theory, observing the channel status, a station can estimate the average collision length and the average number of collisions and with a minimization algorithm obtain pmin.
Authors argue that it is unsuitable for run-time and propose a heuristic for the estimation of pmin.
Remember:i) values of p lesser than pmin correspond to the case in which
E [Idle_p] dominates the tv.
ii) values of p greater than pmin correspond to the case in
which collisions dominate the tv.
In theory, observing the channel status, a station can estimate the average collision length and the average number of collisions and with a minimization algorithm obtain pmin.
Authors argue that it is unsuitable for run-time and propose a heuristic for the estimation of pmin.
Remember:i) values of p lesser than pmin correspond to the case in which
E [Idle_p] dominates the tv.
ii) values of p greater than pmin correspond to the case in
which collisions dominate the tv.
pmin approximationpmin approximation
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
With this in mind pmin is close enough to a p value that
satisfies:
E [Coll ].E [Nc ] = (E [Nc ] + 1).E [Idle_p ].tslot
Simplification: for p close to pmin the number of collisions is
stationary and so E [Coll ] can be taken to be constant.
So
with
With this in mind pmin is close enough to a p value that
satisfies:
E [Coll ].E [Nc ] = (E [Nc ] + 1).E [Idle_p ].tslot
Simplification: for p close to pmin the number of collisions is
stationary and so E [Coll ] can be taken to be constant.
So
with
),_(][ cNpIdleCollE ),_(][ cNpIdleCollE
][
][)1][(),_(
c
slotccc NE
tNENENpIdle
][
][)1][(),_(
c
slotccc NE
tNENENpIdle
pmin estimationpmin estimation
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
802.11+802.11+
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Each station start with CW set to the standard CWmin.(authors use the legacy 802.11 draft specs. with CWmin=32)
CW is updated at the end of each tv which contains at least
one collision
Each station runs the algorithm to estimate pmin , and the
estimate of the contention window is now 2 / (pmin –1)
With this the current CW is updated as:CW = a.CW + (1-a).(2 / (pmin –1))
a having the role of a smoothing factor.
Each station start with CW set to the standard CWmin.(authors use the legacy 802.11 draft specs. with CWmin=32)
CW is updated at the end of each tv which contains at least
one collision
Each station runs the algorithm to estimate pmin , and the
estimate of the contention window is now 2 / (pmin –1)
With this the current CW is updated as:CW = a.CW + (1-a).(2 / (pmin –1))
a having the role of a smoothing factor.
802.11+ capacity802.11+ capacity
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
M unknownM unknown
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
Assume a wrong idea for the number active stations…Assume a wrong idea for the number active stations…
Run-time M estimationRun-time M estimation
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005
From lemma 3, equations
denoting Total_Idle_p the average number of empty slots, we derive:
and so:
From lemma 3, equations
denoting Total_Idle_p the average number of empty slots, we derive:
and so:
1)1(
)1(11
M
M
ppM
pNE 1
)1(
)1(11
M
M
ppM
pNE slotM
M
tp
ppIdleE
)1(1
)1(_
slotM
M
tp
ppIdleE
)1(1
)1(_
pM
ppIdleENEpIdleTotal
1
_1__ pM
ppIdleENEpIdleTotal
1
_1__
ppIdleTotal
pM
__
1ppIdleTotal
pM
__
1
Result of estimating MResult of estimating M
CS-539 Mobile Networks & Computing Vangelis Angelakis 23/3/2005