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I-Hong Hou P.R. Kumar

Admission Control and Scheduling for QoS Guarantees for Variable-Bit-Rate Applications on Wireless Channels. I-Hong Hou P.R. Kumar. University of Illinois, Urbana-Champaign. Background: Wireless Networks.

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I-Hong Hou P.R. Kumar

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  1. Admission Control and Scheduling for QoS Guarantees for Variable-Bit-Rate Applications on Wireless Channels I-Hong Hou P.R. Kumar University of Illinois, Urbana-Champaign

  2. Background: Wireless Networks • There will be increasing use of wireless networks for serving traffic with QoS constraints: • VoIP • Video Streaming • Real-time Monitoring • Networked Control 1/30

  3. Challenges • Wireless Network limitation • Non-homogeneous, unreliable wireless links • Client QoS requirements • Specified traffic pattern • Delay bound • Delivery ratio bound • Throughput bound • System perspective • Fulfill clients with different QoS requirements 2/30

  4. Goal of the Paper • Prior work [Hou, Borkar, and Kumar]: • All clients generate traffic with the same rate • Admission control and packet scheduling policies • Q: How to deal with more complicated traffic patterns? • Applications with variable-bit-rate (VBR) traffic • MPEG streaming • Clients generate traffic with different rates • This work extends results to arbitrary traffic patterns 3/30

  5. Client-Server Model • A system with N wireless clients and one AP • Time is slotted • One packet transmission in each slot • AP schedules all transmissions slot length = transmission duration 2 1 AP 3 4/30

  6. Channel Model • Unreliable, non-homogeneous wireless channels • successful with probability pn • failed with probability 1-pn • p1,p2,…,pN may be different 2 p2 1 p1 AP p3 3 5/30

  7. Uplink Protocol • Poll (ex. CF-POLL in 802.11 PCF) • Data • No need for ACK • pn = Prob( both Poll/Data are delivered) Data 2 p2 1 p1 POLL AP p3 3 6/30

  8. Downlink Protocol • Data • ACK • pn = Prob( both Data/ACK are delivered) ACK 2 p2 1 p1 Data AP p3 3 7/30

  9. Traffic Model • Group time slots into intervals with τ time slots • Clients may generate packets at the beginning of each interval {1,.,3} {.,2,.} {1,2,3} τ {1,2,3} {1,.,3} {.,2,.} 2 p2 1 p1 AP p3 {1,.,3} {.,2,.} {1,2,3} 3 8/30

  10. Delay Bound • Deadline = Interval • Packets are dropped if not delivered by the deadline • Delay of successful delivered packet is at most τ {1,.,3} {.,2,.} {1,2,3} τ {1,2,3} {1,.,3} {.,2,.} 2 p2 1 p1 AP arrival deadline p3 {1,.,3} {.,2,.} {1,2,3} 3 9/30

  11. Packet Scheduling {1,.,3} {.,2,.} {1,2,3} forced idleness F {1,2,3} {1,.,3} {.,2,.} 2 p2 S I I 1 p1 dropped AP p3 {1,.,3} {.,2,.} {1,2,3} F S 3 10/30

  12. Timely Throughput • Timely throughput = avg. # of delivered packets per interval {1,.,3} {.,2,.} {1,2,3} F {1,2,3} {1,.,3} {.,2,.} 2 p2 S I I 1 p1 AP p3 {1,.,3} {.,2,.} {1,2,3} F S 3 11/30

  13. Packet Arrivals • Distribution of packet arrivals is specified {1,.,3} {.,2,.} {1,2,3} F {1,2,3} {1,.,3} {.,2,.} 2 p2 S I I 1 p1 AP p3 {1,.,3} {.,2,.} {1,2,3} F S 3 12/30

  14. QoS Requirements • Client n requires timely throughput qn • Delivery ratio requirement of client n = qn /{arrival prob. of client n} {1,.,3} {.,2,.} {1,2,3} F {1,2,3} {1,.,3} {.,2,.} 2 p2 S I I 1 p1 AP p3 {1,.,3} {.,2,.} {1,2,3} F S 3 13/30

  15. Problem Formulation • Admission control • Given τ, packet arrivals, pn, qn, decide whether a set of clients is feasible • Scheduling policy • Design a policy that fulfills every feasible set of clients 14/30

  16. Work Load • The proportion of time slots needed for client n is 15/30

  17. Work Load • The proportion of time slots needed for client n is expected number of time slots needed for a successful transmission 15/30

  18. Work Load • The proportion of time slots needed for client n is number of required successful transmissions in an interval 15/30

  19. Work Load • The proportion of time slots needed for client n is normalize by interval length 15/30

  20. Work Load • The proportion of time slots needed for client n is • We call wn the “work load” 15/30

  21. Necessary Condition for Feasibility • Necessary condition from classical queuing theory: • But the condition is not sufficient • Packet drops by deadline misses cause more idleness than in queuing theory {1,.,3} {.,2,.} {1,2,3} F {1,2,3} {1,.,3} {.,2,.} 2 p2 S I I 1 p1 AP p3 {1,.,3} {.,2,.} {1,2,3} F S 3 16/30

  22. Stronger Necessary Condition • Let IS = Expected proportion of the idle time when the server only works on S • IS decreases as S increases • Theorem: the condition is both necessary and sufficient • Admission control checks the condition 17/30

  23. Largest Debt First Scheduling Policies • Give higher priority to client with higher “debt” {1,2,3} F F S {1,2,3} 2 p2 F 1 p1 AP p3 {1,2,3} F S 3 18/30

  24. Two Definitions of Debt • The time debt of client n • time debt = wn– actual proportion of transmission time given to client n • The weighted delivery debt of client n • weighted delivery debt = (qn– actual timely throughput)/pn • Theorem: Both largest debt first policies fulfill every feasible set of clients • Feasibility Optimal Policies 19/30

  25. Evaluation Methodology • Evaluate five policies: • DCF • Enhanced DCF (EDCF) by 802.11e • PCF with randomly assigned priorities (random) • Time debt first policy • Weighted-delivery debt first policy • Metric: Shortfall in Timely Throughput 20/30

  26. Evaluated Applications • VoIP • Generate packets periodically • Duplex traffic • Clients may generate packets by different period • MPEG • Generate packets probabilistically • Only downstream traffic • Clients may generate packets by different probability 21/30

  27. VoIP Traffic • ITU-T G.729.1 • Bit rates between 8 kb/s to 32 kb/s • Different bit rates correspond to different periods 22/30

  28. VoIP Clients • Two groups of clients: • Feasible set: 6 group A clients, 5 group B clients • Infeasible set: 6 group A clients, 6 group B clients 23/30

  29. VoIP Results: A Feasible Set 24/30

  30. VoIP Results: A Feasible Set fulfilled 24/30

  31. VoIP Results: A Feasible Set 24/30

  32. VoIP Results: A Feasible Set 24/30

  33. VoIP Results: A Feasible Set 24/30

  34. VoIP Results: An Infeasible Set 25/30

  35. VoIP Results: An Infeasible Set small shortfall 25/30

  36. VoIP Results: An Infeasible Set 25/30

  37. VoIP Results: An Infeasible Set 25/30

  38. VoIP Results: An Infeasible Set 25/30

  39. MPEG Traffic • Model MPEG VBR traffic by a Markov chain consisting of three activity states (Martin et al) • MAC: 802.11a 26/30

  40. MPEG Clients • Two groups of clients • Group A generates traffic according to Martin et al and requires 90% delivery ratio • Group B generates traffic half as often as A and requires 80% delivery ratio • The nth client in each group has (60+n)% channel reliability • Feasible set: 4 group A clients, 4 group B clients • Infeasible set: 5 group A clients, 4 group B clients 27/30

  41. MPEG Results: A Feasible Set 28/30

  42. MPEG Results: A Feasible Set fulfilled 28/30

  43. MPEG Results: A Feasible Set 28/30

  44. MPEG Results: A Feasible Set 28/30

  45. MPEG Results: A Feasible Set 28/30

  46. MPEG Results: An Infeasible Set 29/30

  47. MPEG Results: An Infeasible Set small shortfall 29/30

  48. MPEG Results: An Infeasible Set 29/30

  49. MPEG Results: An Infeasible Set 29/30

  50. MPEG Results: An Infeasible Set 29/30

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