exploiting diversity in wireless networks
DESCRIPTION
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. Capacity of Wireless Networks. Limited by Interference Available spectrum - PowerPoint PPT PresentationTRANSCRIPT
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Exploiting Diversity in Wireless Networks
Nitin H. VaidyaUniversity of Illinois at Urbana-Champaign
www.crhc.uiuc.edu/wireless
Presentation at Mesh Networking SummitSnoqualmie, WA, June 23-24, 2004
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Capacity of Wireless Networks
Limited by
Interference Available spectrum
Need to find ways to get most out of availablespectrum
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Diversity / Multiplicity / Heterogeneity
Diversity provides flexibility in using available resources
Can help improve performance
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Diversity / Multiplicity / Heterogeneity
Research Agenda
Abstractions that capture diversity
Protocols that exploit diversity
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Diversity / Heterogeneity
Many dimensions:
Physical layer
Architecture
Upper layer
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Channel Diversity
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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
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Alternative Approach
Exploit protocol characteristics to benefit from the diversity
Examples:•Pipelining
•Backup routes
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Backoff Data / ACKRTS/CTS
Channel contention resolved using backoff(and optional RTS/CTS)
IEEE 802.11
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Backoff Data / ACKRTS/CTS
Unproductive
Backoff keeps channel idle unproductive Most protocols have such idle contention periods
Simple Observation
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Data / ACK
Backoff RTS/CTS Backoff RTS/CTS RTS/CTSBackoff
Data / ACK
Pipelining Using Multiple Channels
Control Channel: Backoff and RTS/CTS Data Channel: Data and ACK
Stage 1
Stage 2
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Pipelining works well only if pipeline stages are balanced !
Data / ACK
Backoff RTS/CTS Backoff RTS/CTS RTS/CTSBackoff
Data / ACK
Control Channel
Data Channel
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Solution: Partial Pipelining
Only partially resolve channel contention in the pipelined stage
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Partial Pipelining
Stage 1: Narrow-Band Busy Tone Channel Stage 2: Data channel
Data / ACK
Backoff RTS/CTS Backoff RTS/CTS RTS/CTSBackoff
Data / ACK
Control Channel
Data Channel
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Partial Pipelining
No packets transmitted on busy tone channel
Bandwidth can be small
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Partial Pipelining
By migrating backoff to a narrow-band channel, cost of backoff is reduced
Data Channel Bandwidth
Busy Tone Channel Bandwidth Backoff Duration
Area = cost of backoff
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Moral of the Story
Looking beyond physical layerdiversity exploitation schemes helps
Protocol characteristics can be exploited
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Another Example
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Multiple Interfaces
Consider devices equipped with both 802.11a and b
802.11a 802.11b
Higher max rate Lower max rate
Lower range Higher range
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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
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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
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Research Agenda
Develop practical protocols that can exploit diversity
Pay attention to protocol characteristics
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Antenna Heterogeneity
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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
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Antenna Heterogeneity
Beamforms: All antennas are not made equal
Timescale: Can beamforms be changed at packet timescales?
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Protocol Design
Protocols designed for “fixed” beam antennas inadequate with “movable” beam antennas
State of the art
MAC Protocols for specific antenna capabilities
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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
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Diversity / Heterogeneity
Many dimensions:
Physical layer
Architecture
Upper layer
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Pure Ad Hoc Networks
No “infrastructure” All communication over (one or more) wireless
hops
EA
B CD
X
Z
Ad hoc connectivity
Y
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Hybrid Networks
Infrastructure + Ad hoc connectivity
EA
B CD
AP1 AP2
X
Z
infrastructure
Ad hoc connectivity
Y
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Hybrid Networks
Infrastructure may include wireless relays
A
CD
AP1 AP2
X
Z
infrastructure
Ad hoc connectivity
Y
B
RP
R
R
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Hybrid Networks
Heterogeneity Some hosts connected to a backbone, most are not Access points/relays may have more processing
capacity, energy
A
CD
AP1 AP2
X
Z
infrastructure
Ad hoc connectivity
Y
B
RP
R
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Heterogeneity Beneficial
Infrastructure provides a frame of reference– Provide location-aware services– Reduce route discovery overhead
AP0 AP1 AP2 AP3
A
B DR2R1 R3
A
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Heterogeneity Beneficial
Reduce diameter of the network Lower delay Potentially greater per-flow throughput
A
CD
AP1 AP2
X
Z
infrastructure
Ad hoc connectivity
Y
B
RP
R
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Infrastructure Facilitates New Trade-Offs (hypothetical curves)
User density distributionaffects the trade-off
Ad hoc-ness
co
nn
ec
tiv
ity
ov
erh
ea
d
Poor Man’s Ad Hoc Network
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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?
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Misbehavior
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Misbehavior
Misbehavior occurs with limited resources
Violating protocol specifications benefits misbehaving hosts
Example: Small backoffs in 802.11 higher throughput
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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
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Conclusions
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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
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Other Research
Distributed algorithms for multi-hop wireless networks
Clock synchronization Message ordering Leader election Mutual exclusion
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Thanks! www.crhc.uiuc.edu/wireless
Advertisement:National Summit for Community Wireless Networks
Urbana-Champaign, IllinoisAugust 20-22, 2004
http://www.cuwireless.net