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2008/11/05 1
Adaptive Fuzzy Controlled Sliding Backoff Scheme
for Optimal Fair Access Wireless Networks
Authors: M. R. M. Rizk et al
Present by: Chien-Chia Chen2008. Nov.05
UCLA CSD
2008/11/05 2
UCLA CSD
Agenda
BEB Recap BEB Fairness Issues Related Work: MACAW Fuzzy Controlled Sliding Backoff Load Estimation Fuzzy membership functions Simulation Results
2008/11/05 3
UCLA CSD
BEB Recap
Binary Exponential Backoff When collision occurs, one picks up a random numb
er T from [1, ], and retransmit after T time slots How to determine
After each collision After each success
BEB
0B
0B
0_ 0_new inc oldB F B 0_ 0_new dec oldB F B
0_ 0_ maxmin 2 ,inc old oldF B B B 0_ 0_ mindec oldF B B
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UCLA CSD
BEB Fairness Issues
BEB tends to favor the node that last succeeds
Losers are likely to lose again and again
data
wait
B0 = 5
B0 = 12
B0 = 2
B0 = 7
data
wait
……Node 1
Node 2
B0 = 7
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UCLA CSD
MACAW
Use MILD (Multiplicative Increase Linear Decrease) instead of BEB
Extend header to carry Every node shares the same
(copy whatever values it heard)
0B
0B
0_ 0_ maxmin 1.5 ,inc old oldF B B B
0_ 0_ minmax 1,dec old oldF B B B
2008/11/05 6
UCLA CSDFuzzy Controlled Sliding Back
off
Use the load estimation as an input to adjust contention window dynamically
Increasing when collision occurs:
Decreasing when tx succeeds:
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UCLA CSD
Load Estimation Pempty_slot = Pr[no access in T] Model the system as a Poisson process
where λ=PATL*g PATL=probability to be permitted to access (assume as 1) g=avg. number of users who want to access per second
(All the above explanations are from Random-Access Control Mechanisms Using Adaptive Traffic Load in ALOHA and CSMA Strategies for EDGE by Mario E. Rivero-Angeles et al. on IEEE Trans on Vehicular Tech., Vol. 54, No. 3, May 2005.)
_
#
#empty slot
Total of Empty SlotsP
Total of Slots
0( )Pr[ ] Pr(0, )
0!
TTT e
noaccess inT T e
_ _
1ln( )ATLP gTT
empty slot empty slotP e e g PT
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UCLA CSD
Fuzzy Membership Functions
g
FSFIncreasement
BSFIncreasement
Small 20% 80%
Medium 40% 60%
High 60% 40%
Very Hign 80% 20%
For example, if g=0.75
Small=0.5Medium=0.5High=0Very High=0
FSF=20%*0.5+40%*0.5=30%
BSF=80%*0.5+60%*0.5=70%
2008/11/05 9
UCLA CSD
Simulation Results On MATLAB Using slotted system (for the convenience to calcula
te Pempty_slot) Don’t know what kind of random access scheme the
y use Every node in the system always has a packet to tra
nsmit Each run contains a fixed number of nodes All nodes are in the same collision domain Bmax=1024 (255 in 802.11b) Bmin=2, 4, 8, 16 (7 in 802.11b)