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Exploiting Diversity in Wireless Networks

Exploiting Diversity in Wireless Networks

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Exploiting Diversity in Wireless Networks

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  1. Exploiting Diversity in Wireless Networks Nitin H. Vaidya University of Illinois at Urbana-Champaign www.crhc.uiuc.edu/wireless Presentation at Mesh Networking Summit Snoqualmie, WA, June 23-24, 2004

  2. Capacity of Wireless Networks Limited by • Interference • Available spectrum Need to find ways to get most out of available spectrum

  3. Diversity / Multiplicity / Heterogeneity • Diversity provides flexibility in using available resources • Can help improve performance

  4. Diversity / Multiplicity / Heterogeneity Research Agenda • Abstractions that capture diversity • Protocols that exploit diversity

  5. Diversity / Heterogeneity • Many dimensions: • Physical layer • Architecture • Upper layer

  6. Channel Diversity

  7. Channel Diversity • Multiple channels can help improve performance • Obvious approaches: • Exploit diversity to choose channel with best gain • Use multiple channels simultaneously to improve capacity • Developing practical protocols for the “obvious” approaches is still a challenge

  8. Alternative Approach • Exploit protocol characteristics to benefit from the diversity • Examples: • Pipelining • Backup routes

  9. IEEE 802.11 • Channel contention resolved using backoff(and optional RTS/CTS) Backoff RTS/CTS Data / ACK

  10. Simple Observation • Backoff keeps channel idle  unproductive • Most protocols have such idle contention periods Unproductive Backoff RTS/CTS Data / ACK

  11. Pipelining Using Multiple Channels • Control Channel: Backoff and RTS/CTS • Data Channel: Data and ACK Backoff RTS/CTS Backoff RTS/CTS Backoff RTS/CTS Stage 1 Data / ACK Data / ACK Stage 2

  12. Backoff RTS/CTS Backoff RTS/CTS Backoff RTS/CTS Pipelining works well only if pipeline stages are balanced ! Control Channel Data / ACK Data / ACK Data Channel

  13. Solution: Partial Pipelining • Only partially resolve channel contention in the pipelined stage

  14. Backoff RTS/CTS Backoff RTS/CTS Backoff RTS/CTS Partial Pipelining • Stage 1: Narrow-Band Busy Tone Channel • Stage 2: Data channel Control Channel Data / ACK Data / ACK Data Channel

  15. Partial Pipelining • No packets transmitted on busy tone channel • Bandwidth can be small

  16. Partial Pipelining • By migrating backoff to a narrow-band channel, cost of backoff is reduced Data Channel Bandwidth Area = cost of backoff Busy Tone Channel Bandwidth Backoff Duration

  17. Moral of the Story • Looking beyond physical layerdiversity exploitation schemes helps • Protocol characteristics can be exploited

  18. Another Example

  19. Multiple Interfaces • Consider devices equipped with both 802.11a and b

  20. Channel Diversity • 802.11b “network” • denser than the 802.11a network • but provides lower rate Example approach: • Use 802.11a as primary network • Use 802.11b network to provide backup routes when 802.11a routes fail • The 802.11b network could be used for other things too

  21. Protocol Interactions • For TCP, route failure more painful than a degradation in available capacity • The backup routes can avoid a route failure • Benefits of added capacity can be magnified by exploiting protocol behavior

  22. Research Agenda • Develop practical protocols that can exploit diversity • Pay attention to protocol characteristics

  23. Antenna Heterogeneity

  24. Antenna Heterogeneity • “Fixed beam” antennas prevalent on mobile devices • Omnidirectional antennas (often with diversity) • Other antennas likely to become more prevalent • Switched, steered, adaptive, smart … • Can form narrow beamforms, which may be changed over time • Re-configurable antennas • Beamforms can be changed over time by reconfiguring the antenna, but not necessarily narrow beams

  25. Antenna Heterogeneity • Beamforms: All antennas are not made equal • Timescale: Can beamforms be changed at packet timescales?

  26. Protocol Design • Protocols designed for “fixed” beam antennas inadequate with “movable” beam antennas • State of the art MAC Protocols for specific antenna capabilities

  27. Research Challenge How to design “antenna-adaptive” protocols ? • Need to develop suitable antenna abstractions that span a range of antenna designs • Forces us to think about essential characteristics of antennas • Example: Variability of beamforms a more fundamental property than directionality

  28. Diversity / Heterogeneity • Many dimensions: • Physical layer • Architecture • Upper layer

  29. Pure Ad Hoc Networks • No “infrastructure” • All communication over (one or more) wireless hops B C D E A Z Ad hoc connectivity Y X

  30. Hybrid Networks • Infrastructure + Ad hoc connectivity infrastructure AP1 AP2 B C D E A Z Ad hoc connectivity Y X

  31. Hybrid Networks R • Infrastructure may include wireless relays infrastructure AP1 AP2 R P C B R D A Z Ad hoc connectivity Y X

  32. infrastructure AP1 AP2 R P C B R D A Z Ad hoc connectivity Y X Hybrid Networks • Heterogeneity • Some hosts connected to a backbone, most are not • Access points/relays may have more processing capacity, energy

  33. A Heterogeneity Beneficial • Infrastructure provides a frame of reference • Provide location-aware services • Reduce route discovery overhead AP0 AP1 AP2 AP3 R3 R2 R1 D B A

  34. infrastructure AP1 AP2 R P C B R D A Z Ad hoc connectivity Y X Heterogeneity Beneficial • Reduce diameter of the network • Lower delay • Potentially greater per-flow throughput

  35. Poor Man’s Ad Hoc Network Infrastructure Facilitates New Trade-Offs (hypothetical curves) overhead connectivity User density distribution affects the trade-off Ad hoc-ness

  36. Research Issues • How to trade “complexity” with “performance” ? • Parameterize ad hoc-ness ? • Should the spectrum be divided between infrastructure and ad hoc components? • What functionality for relays / access points?

  37. Misbehavior

  38. Misbehavior • Misbehavior occurs with limited resources • Violating protocol specifications benefits misbehaving hosts • Example: Small backoffs in 802.11  higher throughput

  39. Research Agenda • Protocols that maximize performance while discouraging/penalizing misbehavior • Challenge: • Wireless channel prone to temporal and spatial variations • Different players see different channel state • Impossible to detect misbehavior 100% reliably

  40. Conclusions

  41. Conclusions • Diversity/Heterogeneity natural to wireless networks • Need better abstractions to capture the diversity • Need protocols that can exploit available diversity • Need to be able to survive misbehavior

  42. Other Research • Distributed algorithms for multi-hop wireless networks • Clock synchronization • Message ordering • Leader election • Mutual exclusion

  43. Thanks!www.crhc.uiuc.edu/wireless Advertisement: National Summit for Community Wireless Networks Urbana-Champaign, Illinois August 20-22, 2004 http://www.cuwireless.net