Achieving MAC Layer Fairness in Wireless Packet Networks

1. Achieving MAC Layer Fairness in Wireless Packet Networks Thyagarajan Nandagopal, Tae-Eun Kim, Xia Gao, and Vaduvur Bharghavan Reviewed and presented by Tomas Henriksson

2. Presentation Outline • Introduction • Contention resolution algorithms • Fairness in IEEE 802.11 • Analytical framework • Proportional Fair Contention Resolution • Summary and future work • My critique

3. Assumed Scenario • Ad hoc wireless network • CSMA/CA like MAC protocol • Good channel sensing and reservation • Overloaded network • Contention resolution by persistence and backoff • Perfect radio channel, no mobility

4. Characteristics of ad hoc network • Spatial contention for the wireless channel • Trade-off between channel utilization and fairness • Inaccurate state information and decentralized control • Algorithms from wireline and cellular systems cannot be used

5. Contention Resolution Algorithms • No clear definition of fairness • Impossible to measure performance • Hard to compare different algorithms • Three algorithms • BEB • MILD • CB-Fair

6. Binary Exponential Backoff • From Ethernet • Backoff counter is doubled upon collision • Backoff counter reset to 1 at success • Highly short-term unfair under high load • IEEE 802.11 uses modified BEB with a base backoff counter and maximum upper bound

7. Multiplicative Increase/Linear Decrease with Backoff Copy • MACAW uses per-flow instead of per-node • Double backoff counter upon collision • Decrease backoff counter with 1 at success • Advertise backoff counter in packet • Other nodes get current contention in region • Goal is to be proportionally per-flow fair • Highly unfair in assymetric networks

8. Combining Persistance and Backoff (CB-Fair) • Double backoff counter upon collision • Halve backoff counter at success • Contend with persistance P • P is a function of the transmitter’s neighborhood as well as of the receiver’s • Highly unconsistent behavior in different time windows

9. Fairness in IEEE 802.11 • Examining in detail the modified BEB • Simulations performed in ns-2 • Three scenarios show three different problems • Assymetric topology • Per-node versus per-flow fairness • Random topology shows long-term and short-term unfairness

10. Asymmetric Topology

11. Assymetric Topology

12. Per-node versus per-flow

13. Per-node versus per-flow

14. Random Topology

15. Random Topology

16. General Framework • 4 steps • Create network topology graph • Create flow contention graph • Create resource contention graph • Maximize utility function

17. Topology Graph 6 nodes and 5 flows (AB, BC, CD, DE, EF)

18. Flow Contention Graph Flows are nodes, Edges indicate contention

19. Resource Contention Graph

20. Maximize Utility Function • ri is channel allocation rate for flow i • pi is contention loss probability experienced by flow i • Factors a and b system wide parameters • Each node must maximize J(ri)=aU(ri)-bpiri • U(ri)=-1/rin, here U(ri)=log(ri) • Utility constant a,penalty constant b

21. Maximize Utility Function • dri/dt=a-bpi/U’(ri) • U(ri)=log(ri) => dri/dt= a-bpi ri • From ref that this all works distributed

22. Proportional Fair Contention Resolution • Observation 1: We can approximate the channel allocation rate with the persistance probability • Observation 2: All flows must have the same backoff counter for fair contention loss distribution in a clique

23. Proportional Fair Contention Resolution

24. Proportional Fair Contention Resolution Performance

25. Summary and Future Work • Fairness is not well defined • Protocols used today are not fair • The framework presented can be used derive a contention resolution mechanism • Introduce user mobility • Introduce random channel error

26. My Critique • Good paper • Weaknesses • As they mention user mobility, radio channel • Throughput is affected • Low bitrate high priority traffic • Flows only one hop • Mathematical proof is peculiar