wireless resource management through packet scheduling outline for this lecture o identify the...
TRANSCRIPT
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Wireless Resource Management through Packet Scheduling
• Outline for this lecture identify the design challenges for QoS support
over wireless mobile networks an initial solution ongoing research
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Environment: Packet Cellular Networks
Base Station
Fixed Host
Wireless Cell
Backbone
Mobile Host
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Refresh your memory: Packet Scheduler
Select the next packet for transmission
Endhost
switch
Scheduling: Achieving QoS at the packet level time scaleScheduling: Achieving QoS at the packet level time scale
InputLink
FabricOutputLink
Scheduler
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Issues for Wireless Packet Scheduling
• #1: Location-dependent wireless channel error
backbone
MH #1
MH #2
Base Station
Sender
Scheduling policy
Channel state
21
2
1
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Issues for Wireless Packet Scheduling
#1 a channel state unware scheduler may schedule wrongly
#2 channel capacity for each user is dynamically changing
• #1: Location-dependent wireless channel error
backbone
21MH #1
MH #2
Base Station
Sender
Scheduling policy
2
1
Channel state
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• #2: Bursty wireless channel error
Observation 1: case for accurate channel state estimation Observation 2: case for deferring transmission
Issues for Wireless Packet Scheduling
[Source: D. Eckhardt, P. Steenkiste, “A trace-based evaluation of adaptive error correction for a wireless LAN,” ACM
MONET, 1998]
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• #1: Location-dependent wireless channel error
• #2: Bursty wireless channel error
• #3: MHs do not have global channel state for scheduling
• distributed scheduling• #4: MHs are often constrained in terms of processing power
• “dumb terminal, smart base stations”
• #5: Contention in channel access among MHs Close interaction among scheduling and Medium Access Control (MAC)
Issues for Wireless Packet Scheduling
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Goals for Wireless Packet Scheduling
• Throughput: Short-term throughput bounds for flows that perceive error free channel Long-term throughput bounds for flows that perceive bounded channel error
• Fairness: Short-term fairness for flows that perceive clean channel Long-term fairness for flows that perceive bounded channel error
Goal: Provide channel-conditionedQoS for multimedia over wireless
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A Comprehensive Quality of Service Model for Wireless Packet Scheduling cont’d.
• Channel-conditioned delay bounds for packets
• Support for diverse applications: Both delay-sensitive and loss-sensitive applications Accept flows with different decoupled delay/bandwidth requirements
optimization of the schedulable region
Graceful service degradation and compensation
Goal: Provide channel-conditionedQoS for multimedia over wireless
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Conventional Approaches for Wireless Packet Scheduling
• #1: FIFO, WRR, etc.: do NOT address wireless link issues Location dependent channel error Bursty channel error inefficient link utilization users are exposed to all channel errors
• #2: address wireless link issues but NO QoS P. Bhagwat et. al. “Channel State Dependent Packet
Scheduling (CSDPS)”, INFOCOM’96 Not able to support multimedia and provide fair service
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Two Design Principles for QoS oriented Wireless Packet Scheduling
• #1: Fair Queueing providing QoS in the error-free case
• #2: Adaptation to location dependent and bursty
channel error via compensation addressing wireless link issues
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Introduction to Wireline Fair Queueing
• A popular paradigm to achieve QoS at the packet level throughput guarantees packet delay guarantees fairness various algorithms, WFQ, WF2Q, SCFQ, STFQ, ... ...
• Key idea: flow separation a fluid fair queueing system packetized approximation of the fluid model works regardless of differences in packet size
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Review: Wireline Fair Queueing Cont’d
F1
F2
F3
F1: weight = 0.25
F2: weight = 0.5
F3: weight = 0.25
t=1t=0 t=2
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Review: Wireline Fair Queueing Cont’d
F1
F2
F3
1/2
1/4
1/4
F1: weight = 0.25
F2: weight = 0.5
F3: weight = 0.25
t=1t=0
Key Idea: Complete flow separation !
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Fair share of excess resources
Review: Wireline Fair Queueing Cont’d
F1
F2
F3
t=1t=0
1/2
1/4
1/4 1/3
2/3
F1: weight = 0.25
F2: weight = 0.5
F3: weight = 0.25
t=2
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t [0,1]
backbone
Base StationSender1/3
2/3
Equal weights
t=0 1 F1
F2
Why Wireline Fair Queueing Fails in Wireless Networks
F3: CBR
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backbone
Base StationSender1/3
2/3
Equal weights
F1
F2
Why Wireline Fair Queueing Fails in Wireless Networks
1/3
1/31/3
t=0 1 2
Instantaneous fairness is NOT equal to long term fairness !
“Memoryless” allocation of WFQ --> no fairness among F1, F2 and F3 !
F3: CBR
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How to adapt to wireless channel conditions and provide QoS ?
• Approach: book-keeping the (recent) history of channel allocation and explicitly controlling future allocations
Channel swapping & compensation
t [1,2]
backbone
Base StationSender
2/3
1/31/3
2/3
Equal weights
t=0 1 2F1
F2
F3: CBR
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Case for Graceful Compensation
• To prevent flow starvation over a short time scale
backbone
Base StationSender1/31/3
2/3
t=0 1 2 3
Equal weights
F1
F2
F3: CBR
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A Comprehensive Wireless QoS Model • Throughput:
Short-term throughput bounds for error-free flows Long-term throughput bounds for error-prone flows
• Fairness: Short-term fairness for error-free flows Long-term fairness for error-prone flows
• Channel-conditioned delay bounds for packets
• Support for both delay sensitive & loss sensitive applications
• Delay and bandwidth decoupling
• Graceful Service Degradation and Compensation: Graceful service degradation for leading flows Graceful service compensation for lagging flows
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Unified Framework for Wireless Fair Queueing: Key Components
• Error-Free Service Model: defines an ideal fair service model assuming no channel error
• Lead and Lag Model: how much service a flow should relinquish or get compensated by
• Compensation Model: compensate for lagging flows at the expense of other flows
• Slot Queues and Packet Queues: support for both delay sensitive and loss sensitive flows in a framework
• Channel State Monitoring and Estimation
• MAC design
Error-free service
Channel state estimation
Lead &lag model
Compen.model
MAC
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A Flow Chart for
the Architecture:
how the components
interact
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A Few Wireless Scheduling Algorithms
• Channel State Dependent Packet Scheduling (CSDPS) and its enhanced version (CBQ-CSDPS)
• Idealized Wireless Fair Queueing (IWFQ) and its variant WPS
• Channel-condition Independent Fair Queueing (CIF-Q)
• Server Based Fairness Approach (SBFA)
• Wireless Fair Service (WFS)
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Component #1: Error Free Service Model
Serves as an “ideal” service model that characterizes the
best you want to achieve
In principle, any wireline fair packet scheduling
algorithm is a candidate:• throughput guarantees• packet delay bound• fairness• delay bandwidth decoupling• implementation complexity
Examples: WFQ, WF^2Q, STFQ, SCFQ, ...
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Component #2: Lead and Lag model• Keep track of the difference between
service that each flow should receive in the error-free service model
accumulative service that each flow has actually received over the error-prone wireless channel
• Classify a flow as “lead,” “lag,” or “in-sync” accordingly• A flow’s status (i.e., leading, lagging, in-sync) can
dynamically change with time• a small catch in the above definition: for some slots, what
about the case when no flow can transmit (i.e. error prone for all flows)
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Lead and Lag Model: An Alternative Definition
• A flow updates its lag if all 3 conditions hold: it is allocated a slot for transmission, it is unable to transmit due to channel error another flow can transmit in current slot and is
willing to give up a slot later
• A flow updates its lead if all 3 conditions hold: another flow gives up its slot due to channel error it uses the slot given up by the error-prone flow it is willing to give up a slot in future to compensate
other flows
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Example: Lead and Lag Model
backbone
Base StationSender
F1
F21 2 3
1 2
1 2 3
4
41
t=0
3
Error Free Service: WFQ
r=1/3
r=1/3
r=1/3
Real Service
F1: lag = 0
F3: CBR
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Example: Lead and Lag Model
backbone
Base StationSender
F1
F21 2 3
1 2
1 2 3
4
41
t=0
3
Real Service
Error Free Service: WFQ
r=1/3
r=1/3
r=1/3
F1: lag = 0
1
1
1
1
2 2
2 3
2
2
3
4 5
3
3
3
F1: lag = 2F2: lead = 2
F3: CBR
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Further Subtle Issues in Lead/Lag Model
• Who should receive the “extra” service that is given up by error-prone flows ? Equal treatment: any flow that perceives a clean
channel Preferential treatment: lagging flows first,
leading flows next, in-sync flows last
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Component #3: Compensation Model• Knowing the lead and lag of an individual flow, how
to compensate lagging flows at the expense of leading flows ?
• Control the compensation process: who participate ?
• All flows ?
• Only leading and lagging flows ? when to compensate ?
• Immediate or deferred How fast to compensate ?
• As quick as possible
• in a more controlled manner: graceful service
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Component #3: Rate Compensation for Leading Flows in WFS
Slot selection based onminimum service tag
Tra
nsm
it
Com
pens
atio
nAggregate
compensation slots
T
rans
mit
Com
pens
atio
n
• flow i hierarchically decomposes into two flows i: ic and it
• compensation flow ic with rate ri E(i)/Emax(i)
• transmission flow it with rate ri(1-E(i)/Emax(i))
Leading flows
Exponential service degradation during compensation !
Transmit
time
rate
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Component #3: Rate Compensation for Lagging Flows in WFS
Slot selection based onminimum service tag
Tra
nsm
it
Com
pens
atio
nAggregate
compensation slots
T
rans
mit
Com
pens
atio
n
Tra
nsit
Tra
nsit
Tra
nsit
WRR for lagging flows
• service comes from normal rate compensation
• maintain a compensation WRR among lagging flows
• traverse WRR when a compensation slot is available
• fair compensation among lagging flows
Leading flows Lagging flows Insync flows
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Example: Graceful Service Degradation in WFS
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Example: Non-graceful Service Degradation in IWFQ
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CSDPS
• Error-free service: WRR is a choice
• Lead & Lag model: no
• compensation model: no
• comments: implications for no compensation: no long-term
fairness, in-sync flows got disturbed, lagging flows have to play luck, etc.
if high-level enforcement is available, may still work
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IWFQ
• Error-Free Service: WFQ
• Lead and lag model: yes
• compensation model: maintaining the tagging history -> maintain the
precedence for channel access serve the packet with minimum tag -> earliest lag
first
• comments: if lag is large, may starve other flows
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CIF-Q
• Error-free service: STFQ
• Lead & Lag model: yes
• Compensation: leading flow receives a fixed fraction lagging flows receives compensation according
to their rate weights
• Comments: linear service degradation for leading flows
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SBFA
• Error-free service: WFQ is a choice
• lead & lag model: no notion of leading flows
• Compensation model: reserve a fraction of bandwidth for compensation
-> a virtual compensation flow any lag is charged to this compensation flow.
• Comments: fundamentally different from others compensation capture effect, HOL blocking, ...
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Summary
How to perform packet scheduling over wireless
• necessary components for wireless fair queueing
• interaction with MAC layer
Wireless Fair Packet Scheduling = Fair Queueing+ Adaptation to wireless channel characteristics
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Scheduling in Multihop Wireless Networks
• Key issue: distributed packet scheduling
• Solution approaches: Backoff based design Table-driven approach
• Illustration through an example