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Networked Media Lab. 1
Weighted Backpressure Scheduling in IEEE 802.11 Wireless Mesh Networks
Jaeyong Yoo
23-11-09
Networked Media Lab. 2
Background-Link / Packet Scheduling-
N1
N2 N5
N7 N6
N4Sender 1
Receiver 1
Sender 2 Receiver 2
• Packet Scheduling– Which queue should be serviced first?
• Link Scheduling– Which link should be activated first?
• Objective– Throughput optimal– Fairness optimal– Stability Achievable Rate of S1
(Red Flow)
Ach
ieva
ble
Rat
e of
S2
(Blu
e Fl
ow)
Objective 1.Throughput Optimality
Objective 2.Fairness Optimality
Objective 3.Stability
Networked Media Lab. 3
Scheduling Research MapNotation: My queue length=X, upstream queue length=Y
MWS(Maximum Weight Scheduling)
a.k.a Back-pressureScheduling
GMS(Greedy Maximal
Scheduling)
Schedule policy: X - Y
’92 TAC
‘95 UCB
Throughput efficiencyof GMS
‘09 Mobihoc
Distributed GMS
‘06 INFOCOM
Capacity Region ofGMS
‘08 INFOCOM
Interference Condition GMS
‘08 INFOCOM
Schedule policy: X(a.k.a no message passing)
Tradeoff study betweenMessage passing vs no message passing
‘08 Mobihoc
Scheduling without“frequent” message passing
‘09 TWC
Q-CSMA
Yet Published
Schedule policy: Y
EZ-flow
‘09 CoNEXT
Implemented System2009 INFOCOM: DiffQ
Implemented System2008 Mobicom: Horizon
Scheduling Policy Evolves
TimeFlies
Schedule policy: βX + γY
(WBS)Weighted
BackpressureScheduling
Networked Media Lab. 4
Motivational Argument
• Queue non-stability while applying backpressure in IEEE 802.11 wireless mesh networks
• Query: Why non-stability comes? Despite the fact that many articles say backpressure is stable!
– Previous implementation work DID NOT provide rigorous analysis on this part
– Hence, we are doing this
– Anyway, what is our major suspect?
Networked Media Lab. 5
Suspect: Implementational approximation
Network of Dream
Theory to Practical
Link-schedulingAssumption 1:
Globally synchronized slotted access
Link-scheduling Assumption 2:
Perfect link schedule(At least
fine-grained priority access)
Link-schedulingAssumption 3:
Immediate Link Schedule
Many implicit assumption(Do not agree with reality)
IEEE 802.11-based Wireless Mesh Networks
Backpressure Backpressure
Link-scheduling Assumption 2:
Quantized Priority Access
(4 levels) Link-scheduling Assumption 2:Priority queue
(Queuing delay)
Approximation arrow
Approximation arrow
Many other constraints(Even “currently unknown”)
Networked Media Lab. 6
Main Argument
• Under the following conditions, – Quantized Priority Link Access, – Scheduling Time Delay (MAC layer queuing delay), and– Heterogeneous Link Qualities,
• Backpressure (X-Y) does not provide stable network queues
• But, βX + γ Y, with β < - γ– There exists values (β, γ, β < - γ) that stabilize network queues
– Under the following conditions• Quantization Level > 2• Any scheduling time delay• “non-critical” link-quality heterogeneity, a.k.a drift
Networked Media Lab. 7
System Model
• General n-hop case– Throughput model
– Queue evolution model
– Define drift• Difference between two adjacent link’s throughput
– Configurable queue limit: C, quantization step: L
),(),( 11 iiiik NNU
Abstract factor that contains link errors and
other flow impact
Networked Media Lab. 8
Main Result of 2-hop case
• In 2-hop case– Under the drift condition of “non-critical” drift
– If beta and gamma satisfies below two conditions,the network queue becomes stable
– With converging point to
],1[,|,~~
||| njiTTU jik
Networked Media Lab. 9
Let’s validate
• Experimental Validation Method– Implement the described system– By changing beta & gamma, observe the behavior
Networked Media Lab. 10
System Implementation
madwifi
Priority queues
Bypassing (Using PF_PACKET + RAW_SOCK + IPPROTO_RAW)Kernel
Click
f1 f2 f3 f4 f5Q Q Q Q QPer
Flowtable
Sched
P P P P P
Choose Highest Schedule Priority
athhal
Antenna
• A view of a router below IP layer
Scheduling Determination
Taken
Scheduling Action Taken
Discrepancy ofScheduling time
Networked Media Lab. 12
System Implementation (cont’d)
• Notable bugs– Unordered packet delivery
• Unordered queue length monitor [fixed by filtering through ID field of IP header]
– Madwifi 5th queue problem• 5th queue has much higher access probability even if we
change cwmin
Networked Media Lab. 13
Experimentation Env.
• Experimentation time = 3 minutes• Change beta and gamma (step 0.2)
– 0 <= Beta < 2– -2 < Gamma <= 0– Total 121 points
• C = 100• L = 30• Madwifi Priority queues: 8 queues• Manipulate channel quality change by inserting random error
– Drift (Up and Down drift)
Networked Media Lab. 14
Beta, Gamma, Out of range
• Mis-configuration of Beta and Gamma
(2, -1.8)
(1.2, -1.0)
(0.4, -0.2)
Networked Media Lab. 15
Beta, Gamma, Out of range(Deep Inside)
• Inside of [0.4, -0.2], C=100
N1 RET
N2 RET
N1 MAC
N2 MAC
N2 Queue
N1 monitoredQueue
Networked Media Lab. 16
Beta, Gamma, Out of range(Deep Inside)
• Inside of [0.4, -0.2], C=100
N2 Queue
N1 monitoredQueue
QuantizedPrioritySpace
Networked Media Lab. 17
N1 RET
N2 RET
N1 MAC
N2 MAC
N2 Queue
N91monitoredQueue
Beta, Gamma, In range(Deep Inside)
• Inside of [0.6, -0.2], C=100
Networked Media Lab. 18
Beta, Gamma, In range(Deep Inside)
• Inside of [0.6, -0.2], C=100
N2 Queue
N1 monitoredQueue
QuantizedPrioritySpace
Link-error impulse
Networked Media Lab. 19
Beta, Gamma, In range(Deep Inside: Drift changing)
N2 Queue
N1 monitoredQueue
QuantizedPrioritySpace
• Inside of [0.6, -0.2], C=100Drift direction changing point
Networked Media Lab. 20
Overall Comparison• From Model (Dark point represents stable point)
Gamma0-2
Beta
0
2
Networked Media Lab. 21
Overall Comparison (cont’d)• Average Queue length• (Drift Down)
• Average Queue length• (Drift Up)
Networked Media Lab. 22
Overall Comparison (cont’d)• Deviation Queue length• (Drift Down)
• Deviation Queue length• (Drift Up)
Networked Media Lab. 23
Conclusion
• Very first analysis of queue stability with considering real-world constraint– Three constraints
• Delay, Drift, Quantized Priority Space
– Provides rule of thumb
• Next step– Analysis is focusing on “averaged behavior”
– What about network variance?
– Will narrow down the choice of beta and gamma
• Adaptive algorithm that finds beta and gamma
Networked Media Lab. 25
Scheduling Framework
Node j
<n per-flow queues>
Node j-1 Node j+1
qj,1 qj,n
q( qj,1, Qj+1,1)Qj,1
p(qj,1, Qj+1,1)Pj,1
Qj+1, 1Qj, 1
qj-1,1 qj-1,n qj+1,1 qj+1,n
qj,i means queue length of node j of i flow
Pj,i means the priority of node j of i flow
Networked Media Lab. 26
Positioning Under Scheduling Framework
†. Two functions q, p can describe various invariants of packet scheduling
1. Back-pressure scheduling[ q(x, y) = x ] [p(x, y) = x – y ]
2. Ez-Flow[ q(x,y) = x] [p(x, y) = -y]
3. PNCP[ q(x,y) = (x+y)/2] [ p(x, y) = x – y ]
4. No-message passing[ no necessary of q] [ p(x, y) = x ]
5. Our proposal[q(x,y) = x + αy] [q(x, y) = βx + γy]
Networked Media Lab. 28
Physical Behavior with Three Conditions
L
0 t
C
t
Priority
Queue len
Ctb )(
)( dtbC
Send Faster
d
d
S
R
Networked Media Lab. 29
Imagine of slotted contention status - 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1 0
Delay = 6C=5
[C-1 = 5] [7-C = 2] N1 wins[C-2 = 3] [8-C = 3] Let’s say N1 wins
[C-3 = 2] [7-C = 2] Let’s say N1 wins
[C-4 = 1] [8-C = 3] Let’s say N2 wins[C-5 = 0] [7-C = 2] Let’s say N2 wins
[C-6 = -1] [6-C =1] Let’s say N2 wins[C-7 = -2] [5-C =0] Let’s say N2 wins
[C-8 = -3] [4-C =0] Let’s say N2 wins[C-7 = -2] [3-C =-2] Let’s say N1 wins
Going up at b=3
Networked Media Lab. 30
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1 0
Delay = 6C=5γ :0.5
[C-0.5 = 4.5] [7-2.5 = 4.5] Let’s say N1 wins[C-1 = 4] [8-2.5 = 5.5] N2 wins
[C-1.5 = 3.5] [7-2.5 = 4.5] N2 wins
[C-2 = 3] [6-2.5 = 3.5] N2 wins[C-2.5 = 2.5] [5-2.5 = 2.5] Let’s say N1 wins
[C-3 = 2] [4-2.5 = 1.5] Let’s say N2 wins
Going up at b=3
Imagine of slotted contention status - 2