1. End-to-End Performance and Fairness in Multihop Wireless Backhaul Networks V. Gambiroza, B. Sadeghi, and E. Knightly Rice University

2. Violeta Gambiroza Backhaul Networks Internet Backhaul network Residential user or small business Backhaul networks technologies –Wireline: coax-, copper-based, fiber –Wireless

3. Violeta Gambiroza Wireless Backhaul Networks TAP Networks Multihop wireless infrastructure –High bandwidth, good economics, deployability Transit Access Point (TAP) Residential user or small business Wireless Backhaul Network Internet

4. Violeta Gambiroza Fundamental Scenario One branch of the access tree Internet TAP1 TAP2 TAP3 TAP4 Traffic matrix –Traffic to and from Internet

5. Violeta Gambiroza Parking Lot Scenario Similar to parking lot with one exit Internet TAP1 TAP2 TAP3 TAP4

6. Violeta Gambiroza Fairness Problem

7. Violeta Gambiroza Fairness Problem

8. Violeta Gambiroza Fairness Problem Goal Ensure equal shares independent of spatial location We need multihop fairness

9. Violeta Gambiroza Contributions Fairness reference model Performance study –TCP –Inter-TAP fairness algorithm Capacity and fairness Wireless Backhaul Network

10. Violeta Gambiroza Outline Fairness reference model –Limitations of existing models –Fairness objectives –Algorithm solution space Performance study Capacity and fairness Wireless Backhaul Network

11. Violeta Gambiroza Limitations of Existing Fairness Models: Ingress-Egress Flow Granularity Fairness with Ingress-Egress (IE) flow granularity –Provide fair share to each ingress-egress pair Ingress Aggregate (IA) flow granularity Fundamentally different –Provide fairness on both IA and IE flow granularities - Fundamentally different Node corresponds to TAP – TAP is small business/residence  Provide fair shares to TAPs independent of number of flows  Treat TAP’s traffic as a single aggregate Ingress-Egress flow granularity Ingress Aggregate flow granularity Ingress-Egress flow granularity

12. Violeta Gambiroza Our Objectives (Our Objectives vs. Classical Objectives) Flow granularity –Ingress aggregate (IA) and Ingress-Egress Our ObjectivesClassical Objectives – Ingress-Egress (IE) – Bandwidth – Wired link Depends on fairness model Spatial properties – Provide fair shares independent of spatial location – Maximize spatial reuse – flows sufficiently spatially separated can transmit simultaneously Resource –Channel access time Medium –Multirate shared wireless channel Formal definition in paper

13. Violeta Gambiroza Problem Statement Fairness reference model defined Distributed algorithm –Targeted at achieving shares defined by reference model Solution space – Local solution – insufficient  Example: Parking lot – Multihop solution  Flow e2e – TCP  Multihop wireless network e2e – Inter-TAP Fairness Algorithm (IFA)

14. Violeta Gambiroza Outline Fairness reference model Performance study –Performance factors –TCP fairness –Inter-TAP Fairness Algorithm (IFA) Capacity and fairness Wireless Backhaul Network

15. Violeta Gambiroza Performance Factors (1/2) Factors investigated Fairness algorithms –Uncontrolled UDP, TCP, IFA Media access control –802.11 with two-way and four-way handshake Antenna technologies –Omni directional, sector Carrier sense range, multiple topologies and flow scenarios… Other simulation specs Channel rate constant 2 Mb/sec 1000 byte packets Goal Study end-to-end performance and fairness

16. Violeta Gambiroza Performance Factors (2/2) Well understood topologies Increased no. of hops from destination Reduced throughput Increased no. of source-dest. pairs Reduced throughput Topology

17. Violeta Gambiroza Performance Factors (2/2) Parking lot MU-TAP and TAP-TAP transmissions on orthogonal channels Internet TAP1 TAP2 TAP3 TAP4 TA(1) TA(2) TA(3) Topology

18. Violeta Gambiroza Fairness with TCP MAC, Hidden Terminals and Information Asymmetry Idealized objective –Assumes perfect collision- free MAC ACK Traffic MUs generate long lived TCP-Sack flows Carrier sense range = transmission range TAP1 TAP2 TAP3 TAP4

19. Violeta Gambiroza Fairness with TCP MAC, and Hidden Terminals and Information Asymmetry ACK Traffic MUs generate long lived TCP-Sack flows Carrier sense range = transmission range TAP1 TAP2 TAP3 TAP4 TAP 1 and TAP 2 traffic starved –Both are hidden terminals –Timeouts – significant throughput penalty  TCP generates bursts of packets

20. Violeta Gambiroza Fairness with TCP MAC, and Hidden Terminals and Information Asymmetry RTS/CTS exchange introduces information asymmetry [KSSK02] –TAP1 has no information of TAP3-TAP4 trans. ACK Traffic MUs generate long lived TCP-Sack flows Carrier sense range = transmission range TAP1 TAP2 TAP3 TAP4 Capacity and fairness need to be considered jointly –Total is up to 125% of objective while two flows are starved

21. Violeta Gambiroza TCP and Sector Antennas MUs generate long lived TCP-Sack flows TAPs use sector antennas TAP1 TAP2 TAP3 TAP4 ACK Traffic Impact of hidden terminals and information asymmetry mitigated Severe spatial bias –TAP 1 traffic obtains 26% of objective Total goodput increased Total goodput is 67% of the objective

22. Violeta Gambiroza Inter-TAP Fairness Algorithm (IFA) Idealized version of algorithm –Omniscient calculation of fair rates  Practical algorithm needs messaging Limit traffic rate at ingress

23. Violeta Gambiroza TCP and IFA MUs generate long lived TCP-Sack flows Carrier sense range = transmission range TAP1 TAP2 TAP3 TAP4 End-to-end performance considerably improved –TAP-aggregated throughput is 59% to 75% of the objective Hidden terminal problem mitigated – Contention considerably decreased –TCP cannot inject bursts of packets ACK Traffic Spatial bias – IFA alone cannot eliminate it Rates lower than the objective

24. Violeta Gambiroza Inter-TAP Performance Isolation Provide inter-TAP performance isolation independent of traffic types ACK Traffic TCP achieves 64% of idealized objective, while UDP obtains 75% Even with balanced contention TCP reduces its rate –Having more MUs per TAP TCP performance degraded Each TAP has one MU TAP1: MU transmits TCP traffic TAP2 and TAP3: MU transmits UDP traffic TAP1 TAP2 TAP3 TAP4

25. Violeta Gambiroza Summary of Findings (1/2) Starvation of upstream flows (UDP, TCP, with or w/o RTS/CTS) –“Parking Lot” scenario results in hidden terminals and information asymmetry Sector antennas and carrier sense range mitigate the hidden terminal problem –Severe spatial bias  SA: Throughput as low as 26% of targeted values  CSR: Throughput as low as 34% of targeted values TCP able to exploit spatial reuse

26. Violeta Gambiroza Summary of Findings (2/2) IFA approximates reference model performance The impact of hidden terminal problem and information asymmetry mitigated –Without any modifications to CSMA/CA TCP over IFA achieves 59% to 75% of idealized objective –Without any modifications to TCP Inter-TAP performance isolation

27. Violeta Gambiroza Outline Fairness reference model Performance study Capacity and fairness –Maximum throughput without fairness –Fairness objectives and throughput Wireless Backhaul Network

28. Violeta Gambiroza Problem Statement Compute maximum aggregate throughput –No fairness constraint System model –One transmission possible at time –Perfect collision-free MAC Single contention neighborhood

29. Violeta Gambiroza Aggregate Throughput with and without Fairness Constraints Assign time-shares to maximize network throughput Fairness constraints Temporal fairness constraint Spatial bias removal constraint Ingress aggregate constraint No spare time-capacity Solution:

30. Violeta Gambiroza Conclusions Fairness Fairness reference model formally defined Designed for multihop wireless networks Performance study Starvation of upstream flows Sector antennas, larger carrier sense range, IFA mitigate the problem IFA approximates performance of reference model Capacity and fairness Need to be considered jointly

31. End-to-End Performance and Fairness in Multihop Wireless Backhaul Networks V. Gambiroza, B. Sadeghi, and E. Knightly Rice University