ISSUES IN WIRELESS MAC PROTOCOLS

1. ISSUES IN WIRELESS MAC PROTOCOLS Mohit Virendra Peng Lin Vidhya Seran

2. OUTLINE • MAC Fairness in Wireless Ad-Hoc Networks • MAC Fairness in Wireless Cellular Networks • Power Controlled Multiple Access Protocol for Wireless Ad-Hoc Networks

3. Why Mac Fairness? • Mobile Stations share a common broadcast channel. • Existing protocols cannot prevent the “Capture Effects” • Hidden Terminal Problem and Exposed Terminal Problem. • Tradeoff between fairness and channel utilization

4. Fairness:Various Approaches • 1.DFWMAC (IEEE 802.11 std.) [1] • 2.MACAW :Improvement over MACA (Multiple Access Collision Avoidance) [2] • Distributed Fair Scheduling • Flow-Graph Based Approach etc. • Estimation Based Fair Medium Access: Improvement over earlier approaches. (based on MACAW and DFWMAC)

5. Brief Overview of MACAW • Uses modified RTS-CTS-DS-DATA-ACK message exchange. • Uses modified BEB algorithm(milder): Collision:Finc(x)=MIN[1.5x,BOmax] Success:Fdec(x)=MAX[x-1,BOmin] • Per Stream fairness not Per Station (allocates bandwidth equally to streams and not stations) • Results in 37% throughput improvement with 6% overhead addition over MACA.

6. Problems with MACAW: • In above configuration when load increases to a certain degree,st3 captures channel and st2 suffers degradation in throughput • Backoff Copy scheme works only when congestion is homogeneous

7. Estimation based Fair Medium Access: Notations: • Ø(i) :A predefined fairshare that station i should receive • W(i) :The actual throughput achieved by station i. • L(i) :Station i’s offered load

8. Desirable properties • Station i’s offered load to channel is less than capacity: W(i)=L(i) • Station’s offered load> Capacity: each station should be able to get its fair share of the channel,i.e. prop. to Ø • Thus ideally for i and j: W(i)/ Ø(i)=W(j)/ Ø(j)

9. Description • We define Fairness Index (FI): FI=max{ұ i,j :max[W(i)/Ø(i) ,W(j)/Ø(j)] / min [W(i)/Ø(i) ,W(j)/Ø(j)] } • Actual case: Abs(W(i)/ Ø(i)-W(j)/ Ø(j)) should be bounded by smallest value. • Our Goal: Design a dist MAC protocol that minimizes FI and achieves fairness

10. Description (contd.) • Choice of Ø(i):(open research problem) • Assumption here (no admission control) • Ø(i) = 0.5 (regardless of neighbors) • Ø(o)= 1- Ø(i)=0.5 (per station fairness) • E.g. Station with two active links: Ø(i)/Ø(o) = Ø(i)/(1-Ø(i)) =2/1 Thus Ø(i) ~ 0.67 (per stream fairness)

11. Description (contd.) Back off Scheme Notations: • W(ei):The estimated share of estimating station itself. • W(eo):The estimated share of other stations. • T(type):Time to transmit a packet of type type.

12. How Fair-Share Estimation algorithm works: • Station i sees itself competing with a group of stations for channel access. • Stations dynamically estimate what throughput “they” get and what throughput “others” get and adjust their contention window according to the FI. • Station i estimates “others” bandwidth by looking at the packets in its vicinity • FI(e)=(W(ei)/ Ø(i)) / (W(eo)/ Ø(o)) contd…..

13. The Fair Share Estimation Algorithm

14. HowFair….(contd):Adjustment of Contention Window:

15. How Fair…(contd.):ContentionWindow adjustment • In Algorithm2, C is a constant to adjust adaptivity of the algorithm. • Smaller C:more aggressively contention window adjusted. • C=2, possibility of collision high in high load and large no of competing stations • C close to 1 (1.01), stations busy adjusting their contention windows all the time and algorithm becomes unstable.

16. Simulation and Results(NetWk Configs)

17. Results (contd..)(a) Station throughput (b)fairness index versus station’s offered load for the 4-station scenario.

18. Results (contd..) Station throughput (a)original algorithm (b) modified algorithm

19. Results (contd..) (c)fairness index versus station offered load for the 5 station scenario

20. Results (contd..) (a) Link throughput algorithm (b) link throughput (modified algorithm,Ø=0.5 for all)

21. Results (contd..) (c)link throughput (modified algorithm,Ø=0.67 f0r station 2,3 and 4) (d) FI versus station offered load for the 5-station scenario

22. Results (contd..) (a) Station throughput, (b) fairness index versus station’s offered load for the 6-station scenario.

23. Summary • A different scheme for IEEE 802.11 DFWMAC • Contention window adjustment according to the estimated share . • Achieves far better fairness than others though some throughput sacrificed • Does not assume any knowledge of network topology,thus does not require broadcast packets to disseminate info to other stations:very simple to overlay on existing DFWMAC.

24. OUTLINE • MAC Fairness in Wireless Ad-Hoc Networks • MAC Fairness in Wireless Cellular Networks • Power Controlled Multiple Access Protocol for Wireless Ad-Hoc Networks

25. Wireless Fairness Scheduling Why we need wireless scheduling? Provide short-term fairness Provide short-term throughput bounds Provide delay bounds for packets Decouple delay/bandwidth requirements

26. CSDPS • Channel state dependent packet scheduling algorithm, proposed by P. Bhagwat • One step channel prediction and no compensation • Lagging flows can only make up in long run

27. IWFQ • Idealized wireless fair queueing algorithm, proposed by S. Lu, V. Bhaghavan and R. Srikant • Lagging flows will capture the channel whenever they perceive clean channels

28. CIF-Queueing • Channel independent fair queueing Algorithm, proposed by T.S. Ng, I. Stoica and H. Zhang • Leading flows relinquish their leads linearly and distribute to lagging flows proportional to their weights

29. SBFA • Server-based fairness approach, proposed by P. Ramanthan and P. Agrawal • Statistically reserve a fraction of the bandwidth, no compensation

30. CBQ-CSDPS • Class-based queueing with channel state dependent packet scheduling • Maintain lead and lag based on the actual number of bytes transmitted during a time window • Lagging flows are given explicit precedence, and hence capture the channel

31. Wireless Channel Characteristics • Channel capacity is dynamically time-varying, due to fading/contention • Channel errors are in nature location-dependent and bursty

32. Wireless Fair Service • Scheduling Targets: • Short-term fairness among backlogged flows with clean channels. • Long-term fairness among backlogged flows with bounded channel error • Short-term throughput bounds for flows with clean channels • Long-term throughput bounds for flows with bounded channel error

33. Wireless Fair Service (Cont) • Definitions • Error free service • Lead & Lag Model • Compensation Model • Slot queues & packet queues • Channel monitoring & prediction

34. WFS Service model

35. Error-free service model • A reference for how much service a flow may receive in an ideal error-free channel environment • WFQ is adopted as the error-free service model

36. Lead and lag model • Three types of flows: • Leading flows: the flows which receive excess service • Lagging flows: the flows which relinquish slots due to expected channel errors • In-sync flows: the flows which follow the idealized service model

37. Compensation model • Swapping slots between leading & lagging flows • In-sync flows unaffected • Gradually swapping to avoid the grabbing of the channel

38. Slot queues and packet queues • Separate the logic packet flow queue and the MAC slot queue • Packet flow queue may adopt any packet dropping policy • Slot queue follows the swapping policy

39. Channel monitoring & prediction • Channel errors are highly correlated • One-step prediction: The channel state for the current time slot is predicted to be the same as the monitored channel state for the previous slot

40. Comparison of Wireless Scheduling Algorithms • Scenario: Flow 1 is in error till t = 100 sec, Flow 2 & 3 are always error-free

41. Comparison of Wireless Scheduling Algorithms

42. Comparison of Wireless Scheduling Algorithms(cont)

43. Comparison of Wireless Scheduling Algorithms(cont)

44. Summary • Several wireless fair scheduling algorithms have been proposed to address the fairness issues in wireless networks with time-varying capacity • The performance of such wireless scheduling algorithms depends on the precision of channel monitoring/prediction methods

45. OUTLINE • MAC Fairness in Wireless Ad-Hoc Networks • MAC Fairness in Wireless Cellular Networks • Power Controlled Multiple Access Protocol for Wireless Ad-Hoc Networks

46. MOTIVATION • One of the major issue in wireless networks is developing efficient multiple access protocols that optimizes spectral reuse and hence maximize aggregate channel utilization. • Theoretical studies have shown that ideal medium access protocols using optimal power can improve aggregate channel utilization. • This motivates the study for power controlled wireless medium access protocols.

47. PAST WORK ON POWER CONTROL • Past work on power control has primarily dealt with cellular networks and the base station provides centralized control. • Distributed power control algorithms have also been presented but still require fundamental cellular configuration. • Other work focused on MAC protocols that control transmission power level to conserve power consumption.

48. PCMA • PCMA differs from the related work in two significant ways: • A) Focus on wireless multiple access networks where all nodes share a channel and there is no centralized control. • B) Focus on power control mechanism for increasing channel efficiency rather that as a mechanism for increasing battery life

49. PCMA-contd • Dominant wireless MAC is IEEE802.11 standard follows the CSMA/CA paradigm. • There exists no power control MAC that fits within the collision avoidance framework. • Goal is to propose a power controlled MAC that follow the same collision avoidance framework.

50. PROBLEMS AND APPROACH TO THE SOLUTION • MAC have made the case that a sender receiver pair should first acquire the floor before initiating a data packet transfer. • Acquiring the floor allows sender-reciver pair to avoid collision due to hidden and exposed stations in the shared channel.