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Wireless Resource Management through Packet Scheduling Outline for this lecture o identify the design challenges for QoS support over wireless mobile networks.

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Presentation on theme: "Wireless Resource Management through Packet Scheduling Outline for this lecture o identify the design challenges for QoS support over wireless mobile networks."— Presentation transcript:

1 Wireless Resource Management through Packet Scheduling Outline for this lecture o identify the design challenges for QoS support over wireless mobile networks o an initial solution o ongoing research

2 Environment: Packet Cellular Networks Base Station Fixed Host Wireless Cell Backbone Mobile Host

3 Refresh your memory: Packet Scheduler Select the next packet for transmission End host switch Scheduling: Achieving QoS at the packet level time scale Input Link Fabric Output Link Scheduler

4 Issues for Wireless Packet Scheduling #1: Location-dependent wireless channel error backbone MH #1 MH #2 Base Station Sender Scheduling policy Channel state

5 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 21 MH #1 MH #2 Base Station Sender Scheduling policy 2 1 Channel state

6 #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]

7 #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 á Close interaction among scheduling and Medium Access Control (MAC) Issues for Wireless Packet Scheduling

8 Goals for Wireless Packet Scheduling Throughput: p Short-term throughput bounds for flows that perceive error free channel u Long-term throughput bounds for flows that perceive bounded channel error Fairness: p Short-term fairness for flows that perceive clean channel u Long-term fairness for flows that perceive bounded channel error Goal: Provide channel-conditioned QoS for multimedia over wireless

9 A Comprehensive Quality of Service Model for Wireless Packet Scheduling cont’d. Channel-conditioned delay bounds for packets Support for diverse applications: p Both delay-sensitive and loss-sensitive applications p Accept flows with different decoupled delay/bandwidth requirements á optimization of the schedulable region u Graceful service degradation and compensation Goal: Provide channel-conditioned QoS for multimedia over wireless

10 Conventional Approaches for Wireless Packet Scheduling #1: FIFO, WRR, etc.: do NOT address wireless link issues p Location dependent channel error p Bursty channel error á inefficient link utilization á users are exposed to all channel errors #2: address wireless link issues but NO QoS p P. Bhagwat et. al. “Channel State Dependent Packet Scheduling (CSDPS)”, INFOCOM’96 á Not able to support multimedia and provide fair service

11 Two Design Principles for QoS oriented Wireless Packet Scheduling #1: Fair Queueing á providing QoS in the error-free case #2: Adaptation to location dependent and bursty channel error via compensation á addressing wireless link issues

12 Introduction to Wireline Fair Queueing A popular paradigm to achieve QoS at the packet level p throughput guarantees p packet delay guarantees p fairness p various algorithms, WFQ, WF 2 Q, SCFQ, STFQ, Key idea: flow separation p a fluid fair queueing system p packetized approximation of the fluid model p works regardless of differences in packet size

13 Review: Wireline Fair Queueing Cont’d F1 F2 F3 F1: weight = 0.25 F2: weight = 0.5 F3: weight = 0.25 t=1 t=0 t=2

14 Review: Wireline Fair Queueing Cont’d F1 F2 F3 1/2 1/4 F1: weight = 0.25 F2: weight = 0.5 F3: weight = 0.25 t=1 t=0 Key Idea: Complete flow separation !

15 Fair share of excess resources Review: Wireline Fair Queueing Cont’d F1 F2 F3 t=1t=0 1/2 1/4 1/3 2/3 F1: weight = 0.25 F2: weight = 0.5 F3: weight = 0.25 t=2

16 t  [0,1] backbone Base StationSender 1/3 2/3 Equal weights t=0 1 F1 F2 Why Wireline Fair Queueing Fails in Wireless Networks F3: CBR

17 backbone Base StationSender 1/3 2/3 Equal weights F1 F2 Why Wireline Fair Queueing Fails in Wireless Networks 1/3 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

18 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 1/3 2/3 Equal weights t=0 1 2 F1 F2 F3: CBR

19 Case for Graceful Compensation To prevent flow starvation over a short time scale backbone Base StationSender 1/3 2/3 t= Equal weights F1 F2 F3: CBR

20 A Comprehensive Wireless QoS Model Throughput: p Short-term throughput bounds for error-free flows u Long-term throughput bounds for error-prone flows Fairness: p Short-term fairness for error-free flows u 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: u Graceful service degradation for leading flows u Graceful service compensation for lagging flows

21 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

22 A Flow Chart for the Architecture: how the components interact

23 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)

24 Component #1: Error Free Service Model o Serves as an “ideal” service model that characterizes the best you want to achieve o In principle, any wireline fair packet scheduling algorithm is a candidate: throughput guarantees packet delay bound fairness delay bandwidth decoupling implementation complexity o Examples: WFQ, WF^2Q, STFQ, SCFQ,...

25 Component #2: Lead and Lag model Keep track of the difference between o service that each flow should receive in the error-free service model o 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)

26 Lead and Lag Model: An Alternative Definition A flow updates its lag if all 3 conditions hold: o it is allocated a slot for transmission, o it is unable to transmit due to channel error o 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: o another flow gives up its slot due to channel error o it uses the slot given up by the error-prone flow o it is willing to give up a slot in future to compensate other flows

27 Example: Lead and Lag Model backbone Base StationSender F1 F t=0 3 Error Free Service: WFQ r=1/3 Real Service F1: lag = 0 F3: CBR

28 Example: Lead and Lag Model backbone Base StationSender F1 F t=0 3 Real Service Error Free Service: WFQ r=1/3 F1: lag = F1: lag = 2 F2: lead = 2 F3: CBR

29 Further Subtle Issues in Lead/Lag Model Who should receive the “extra” service that is given up by error-prone flows ? o Equal treatment: any flow that perceives a clean channel o Preferential treatment: lagging flows first, leading flows next, in-sync flows last

30 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: o who participate ? All flows ? Only leading and lagging flows ? o when to compensate ? Immediate or deferred o How fast to compensate ? As quick as possible in a more controlled manner: graceful service

31 Component #3: Rate Compensation for Leading Flows in WFS Slot selection based on minimum service tag Transmit Compensation Aggregate compensation slots Transmit Compensation flow i hierarchically decomposes into two flows i: i c and i t compensation flow i c with rate r i E(i)/E max (i) transmission flow i t with rate r i (1-E(i)/E max (i)) Leading flows Exponential service degradation during compensation ! Transmit time rate

32 Component #3: Rate Compensation for Lagging Flows in WFS Slot selection based on minimum service tag Transmit Compensation Aggregate compensation slots Transmit Compensation Transit WRR for lagging flows service comes from p normal rate p compensation maintain a compensation WRR among lagging flows traverse WRR when a compensation slot is available fair compensation among lagging flows Leading flowsLagging flows Insync flows

33 Example: Graceful Service Degradation in WFS

34 Example: Non-graceful Service Degradation in IWFQ

35 CSDPS Error-free service: WRR is a choice Lead & Lag model: no compensation model: no comments: o implications for no compensation: no long-term fairness, in-sync flows got disturbed, lagging flows have to play luck, etc. o if high-level enforcement is available, may still work

36 IWFQ Error-Free Service: WFQ Lead and lag model: yes compensation model: o maintaining the tagging history -> maintain the precedence for channel access o serve the packet with minimum tag -> earliest lag first comments: o if lag is large, may starve other flows

37 CIF-Q Error-free service: STFQ Lead & Lag model: yes Compensation: o leading flow receives a fixed fraction o lagging flows receives compensation according to their rate weights Comments: o linear service degradation for leading flows

38 SBFA Error-free service: WFQ is a choice lead & lag model: no notion of leading flows Compensation model: o reserve a fraction of bandwidth for compensation -> a virtual compensation flow o any lag is charged to this compensation flow. Comments: o fundamentally different from others o compensation capture effect, HOL blocking,...

39 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

40 Scheduling in Multihop Wireless Networks Key issue: distributed packet scheduling Solution approaches: o Backoff based design o Table-driven approach Illustration through an example


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