M. Heusse, F. Rousseau, R. Guiller and A. Duda SIGCOMM 2005 Slides and Presented by Yong Yang

1. Idle Sense: An Optimal Access Method for High Throughput and Fairness in Rate Diverse Wireless LANs M. Heusse, F. Rousseau, R. Guiller and A. Duda SIGCOMM 2005 Slides and Presented by Yong Yang

2. Problems with IEEE 802.11 DCF • IEEE 802.11 DCF and its most variations • Collision-detection-based access control • Hard to differentiate collision and frame error • Hosts perform back-offs even frame losses are due to bad channel condition (e.g. background noises) • Hard to incorporate physical capture effect • Transmission may succeed even a collision is detected • Using collision, a biased indicator, results in • Low Throughput • Unfairness

3. Overview • Goal: optimize throughput and improve fairness • Approach: use an indicator that is more reliable than collision detection • 1. Key Insight from Channel Contention Analysis • The number of consecutive idle slots under the optimal setting of a network is insensitive to the network size • Consistent view • No global knowledge is needed • 2. Idle Sense Access Method • Nodes detected number of consecutive idle slots • Control the medium access (adjust CW) to make it converge to the theoretically derived value • 3. Nice Properties • Rate Adaptation • Time Fairness

4. Renewal Time Renewal Time Back-off Success Back-off Collision Back-off Tt Tc Analysis of Channel Contention • The transmission attempt probability: β • Prob. that there is no channel activity: Pi = (1 – β)N • Prob. that there is a successful transmission: Pt = n β(1 – β)N-1 • Prob. that there is a collision: Pc = 1- Pt - Pi • Intuitively, the network throughput: • Prob. that a channel activity is a success for node i: Ps|a = β(1 – β)N-1 / [1 –Pi ] • E[back-off] = Pi / (1-Pi) * T slot

5. minimize Given Tc/Tslot (e.g. 68.17 for 802.11b), numerically solve βopt niopt Given Tc/Tslot, denote Numerically computes N The expected number of consecutive idle slots converges quickly: the asymptotic value can be used as a good estimation for a wide range of N ( = 5.68 for 802.11b) The Insight

6. Since , i=0…K Idle Sense Access Method • Each node observes idle intervals between channel activities • Compare with the target value • If > , β β + ε • If < , β  β * α • ε=0.001 and α=5/6 are AIMD coefficients • But, how to control β? • Recalling that β is a function of the collision probability γ • Back-off durations are no longer affected by collisions • AIMD rules for adjusting CW • If > , CW  2 CW / (2+ εCW) • If < , CW  CW / α

7. Nice Properties – Rate Adaptation • Rate adaptation: when frame error rate Perr|a is high, switch to a lower rate (more robust modulation scheme) • How to determine Perr|a ? • No ACK may due to frame error or collision • How to differentiate Perr|a from Pc|a • By idle sense: • Successful transmission rate • Pok=(1–Pc|a)(1–Perr|a)=1 – Pc|a – Perr|a +Pc|aPerr|a≈1 – Pc|a – Perr|a • Pok can be measured online, so Perr|a= 1 – Pc|a– Pok

8. Nice Properties – Time Fairness • Rate diversity leads to performance anomaly • Rate of a slower node limits the throughput of a fast node [proved by A.Kumar] • Time fairness: remove this anomaly by making every node having the similar time for transmission • Achieve time fairness in idle sense • So slower nodes access the channel less often than fast nodes

9. Simulation Results

10. Conclusion and Comments • Analytically show that the idle intervals is insensitive to network size under the optimal settings • Does not consider frame losses due to bad channel condition • E[Back-off] = Pi / (1-Pi) v.s. E[Back-off] = 1 / (1-Pi) • Use AIMD method to adjust CW to make the idle intervals converge to a fixed sub-optimal value • AIMD coefficients, ε and α, do affects the algorithm performance • Enable nodes to estimate frame error rate Perr|a= 1 – Pc|a– Pok • Do not show how fast Pc|a converges to • If not fast, need to estimate N • No simulation result about rate adaptation • Achieve time fairness • Assume other nodes are using the maximum transmission rate (overestimate) • Only applicable to single-cell WLANs

11. Additive Increase Multiplicative Decrease Node 2’s attempt rate Fairness Line Efficiency Line Node1’s attempt rate [D.-M. Qiu & R. Jain 1989]

12. Rate Adaptation • Switch from a higher rate rh to a lower rate rl if • Assume el = 0 and same portion of useful throughput: • How to switch from a lower rate to a higher one? • Other method • Piggyback frame error rate : overhead • Infer from SNR: no obvious correlation

13. Simulation Results 50 nodes Jain Index = Normalized window size = window size / #nodes

14. Convergence Speed 5 nodes transmitting 5 nodes join 5 nodes leave

15. Asymptotically Optimal Backoff • Each node computes the transmission prob. • Na: # attempts for the transmission of a frame • Slot Utilization (SU): • When network utilization reaches its optimal • Postpone transmissions as encountering collisions

16. Slow Decrease • Objective: adapting CW of each node to the current network congestion level • After each successful transmission: • Preserve the exponential back-off mechanism

17. Other DCF Variations • Fast Collision Resolution • Double CW when either collision or loses a contention • Exponentially decrease CW after observing multiple idle slots • Fairly Scheduled Fast Collision Resolution • Set a limit on # successive retransmissions • Binary Counting Down • Require a control channel for scheduling • Proportionally Fair Contention Resolution (MILD) • EIED

18. Rate Adaptation • Auto Rate Fallback • Increase rate after # successful transmission • Decrease rate after # losses • Receiver Based Auto Rate • Receiver piggyback SNR in CTS frames • Assume channel condition remain same • Based on SNR from transmissions at a lower bit rate