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Support mission critical applications ad-hoc network, rooftop-neighbor network sensor network

QoS in ad hoc nets: distributed fair scheduling SCOPE: Self-coordinating Localized FQ H. Luo et al “A Self-Coordinating Approach to Distributed FairQueueing in Ad Hoc Wireless Networks”, Infocom 01. Support mission critical applications ad-hoc network, rooftop-neighbor network sensor network

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Support mission critical applications ad-hoc network, rooftop-neighbor network sensor network

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  1. QoS in ad hoc nets: distributed fair scheduling SCOPE: Self-coordinating Localized FQH. Luo et al “A Self-Coordinating Approach to Distributed FairQueueing in Ad Hoc Wireless Networks”, Infocom 01 • Support mission critical applications • ad-hoc network, rooftop-neighbor network • sensor network • Better coordination to resolve resource competition from inside the network

  2. Challenges I • Location-dependent channel contention • Spatial channel reuse • Distributed scheduling information • Notion of fairness

  3. Challenges II Spatial Channel Reuse F1 X F3 F4 F2 Spatial Collision No Spatial Channel Reuse

  4. F3 F4 F1 F2 Flow Contending Graph Node Graph Flow Contending Graph RTS-CTS-(DS)-DATA-ACK F3 F4 F1 F2

  5. F3 F4 F1 F2 Flow Contending Graph Challenges III • Distributed scheduling information • NO single entity has complete flow information • Fairness notion • No consistent contending flow set • Indirect contention • Conflict with max t’put

  6. Fairness • Flow with minimum service should be guaranteed to receive service • Identify the flow with global minimum service w/o global search? – MLM-FQ • Simultaneous transmissions should be scheduled whenever possible, subject to max-min and BW constraint • EMLM-FQ

  7. MLM-FQMaximize Local Min-FQ • Identify all flows that receive localminimum services • Global minimum must be among local minima • Maximize-global-min => maximize-local-min

  8. MLM-FQ • A node tags its own flows (STFQ) • Piggyback service tags in control messages: • Current service tag in RTS-CTS • Updated service tag in DS-ACK • A node maintains one-hop neighboring flows’ tags – a local table • A node transmits only if one of its flows has the local minimum service tag

  9. F4 F1 be scheduled F3 F1 F2 MLM-FQ F3 3 F4 4 F1 1 F2 2 F4 4 F1 1 F2 2 F3 3 F4 4 F1 1 F2 2 F4 4

  10. F1 F1 1 1 F2 2 F4 F4 1 1 F1 F1 11 1 F2 2 F3 2 F2 2 F3 2 F4 F4 1 11 F1 F1 1 1 F3 2 F4 F4 1 1 Drawbacks • Low channel utilization – spatial reuse may be prohibited • Worst-case C/N • Deadlock due to collisions on service tag propagation

  11. Enhanced MLM-FQ • Set a backoff value for each flow before it contends for channel • Backoff value set to be the total number of flows that have smaller service tags in local table

  12. How E-MLM works

  13. How E-MLM works

  14. EMLM-FQ Min Fair Service • Worst-case: C/Nc • Nc is the total number of flows in the maximum clique of the flow contending graph • Independent from total number of flows

  15. Comparing Scheduling Schemes

  16. FTP/TCP CBR/UDP FTP/TCP Performance Evaluation

  17. Throughputs Aggregate: 141.4kbps Aggregate: 205.8kbps

  18. SCOPE Summary • Ensure fair service to individual flows through localized coordination • Table-driven distributed algorithms • Addresses: • Location-dependent resource sharing – self-coordination frominside the network • Scalability - both state maintenance and communication overhead • Mobility & wireless link dynamics due to outsideinterferences and attacks

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