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TAPs: An Architecture and Protocols for a High-Performance Multi-hop Wireless Infrastructure

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Title: TAPs: An Architecture and Protocols for a High-Performance Multi-hop Wireless Infrastructure


1
TAPs An Architecture and Protocols for a
High-Performance Multi-hop Wireless Infrastructure
  • Ed Knightly
  • ECE/CS Departments
  • Rice University
  • http//www.ece.rice.edu/knightly
  • Joint work with
  • V. Kanodia, A. Sabharwal, and B. Sadeghi

2
The Killer App is the Service
  • High bandwidth
  • High availability
  • Large-scale deployment
  • High reliability
  • Nomadicity
  • Economic viability
  • Why?
  • Broadband to the home and public places
  • Enable new applications

3
WiFi Hot Spots?
  • 11 Mb/sec, free spectrum, inexpensive APs/NICs

Carriers Backbone/Internet
T1
Medium bandwidth (wire), sparse, and expensive
  • Why? poor economics
  • High costs of wired infrastructure (10k
    500/month)
  • Pricing U.S. 3 for 15 minutes CH 0.90
    CHF/minute
  • Dismal coverage averaging 0.6 km2 per 50 metro
    areas projected by 2005

4
Cellular?
  • Cellular towers are indeed ubiquitous
  • Coverage, mobility,
  • High bandwidth is elusive
  • Aggregate bandwidths in Mb/sec range, per-user
    bandwidths at dial-up speeds
  • Expensive spectral fees and high infrastructure
    costs

5
Ad Hoc Networks?
Free but low availability and low bandwidth
  • Availability
  • Problems intermediate nodes can move, power off,
    fade, DoS attack ? routes break, packets are
    dropped, TCP collapses,
  • Low bandwidth
  • Poor capacity scaling
  • Unlike cellular, users consume wireless resources
    at remote locations

6
TAPs Multihop Wireless Infrastructure
  • Transit Access Points (TAPs) are APs with
  • beam forming antennas
  • multiple air interfaces
  • enhanced MAC/scheduling/routing protocols
  • Form wireless backbone with limited wired
    gateways

7
Multihop Wireless Infrastructure
  • Transit Access Points (TAPs) are APs with
  • beam forming antennas
  • multiple air interfaces
  • enhanced MAC/scheduling/routing protocols
  • Form wireless backbone with limited wired
    gateways
  • High bandwidth
  • High spatial reuse and capacity scaling
  • Opportunistic protocols
  • High availability
  • Redundant paths and non-mobile infrastructure
  • Deployability
  • Good economics
  • Unlicensed spectrum, few wires, exploit WiFi
    components

8
Prototype and Testbed Deployment
  • FPGA implementation of enhanced opportunistic,
    beamforming, multi-channel, QoS MAC
  • Build prototypes and deploy on Rice campus and
    nearby neighborhoods
  • Measurement study from channel conditions to
    traffic patterns

9
Outline
  • TAP architecture
  • OAR an opportunistic auto-rate MAC
  • MOAR multi-channel OAR
  • Open problems

10
Motivation
  • Wireless channel is variable

11
Opportunistic MAC Goal
  • Exploit the variations inherent in wireless
    channel to increase throughput
  • Maintain fair temporal shares for different flows
  • Constraint distributed random access protocol

12
IEEE 802.11 Multi-rate
  • Support of higher transmission rates in better
    channel condition
  • 802.11b
  • available rates 2, 5.5, 11 Mbps
  • 802.11a
  • available rates up to 54 Mbps
  • Auto Rate Fallback (ARF)
  • Monteban et al. 97
  • Use history of previous transmissions to
    adaptively select future rates

13
Temporal vs. Throughput Fairness
  • Equivalent in single-rate networks
  • Throughput fairness results in significant
    inefficiency in multi-rate networks
  • Example

14
Temporal vs. Throughput Fairness
  • Equivalent in single-rate networks
  • Throughput fairness results in significant
    inefficiency in multi-rate networks
  • Example

user 1
user 3
access point
user 2
Even 1 user with low transmission rate results in
a very low network throughput
15
Temporal vs. Throughput Fairness
  • Equivalent in single-rate networks
  • Throughput fairness results in significant
    inefficiency in multi-rate networks
  • Example

user 1
user 3
access point
user 2
Same time-shares of the channel for different
flows, also higher throughput
16
Opportunistic MAC
  • Goal
  • Exploit short-time-scale variations inherent in
    wireless channel to increase throughput in
    wireless ad hoc networks
  • Issue
  • Maintaining temporal share of each node
  • Challenge
  • Channel info available only upon transmission

17
Opportunistic Auto Rate (OAR)
  • Observation coherence time on order of multiple
    packet transmission times
  • measure channel quality on RTS/CTS handshake
  • hold good channels for multiple transmissions
  • Ensure fairness by scaling number of packets
    transmitted to channel quality
  • packets Current rate / Base rate
  • with random access, all flows equally likely to
    access channel
  • OAR High throughput, while maintaining temporal
    fairness properties of single rate IEEE 802.11

18
RBAR Protocol
  • Receiver Based AutoRate (RBAR)
  • Receiver controls the senders transmission rate
  • Control messages sent at Base Rate

Reservation Sub-Header
destination
source
19
OAR Protocol
Reservation Sub-Header
  • OAR
  • Once access granted, it is possible to send
    multiple packets if the channel is good

destination
source
20
Performance Comparison
  • IEEE 802.11

R
D1
Transmitter
C
A
Receiver
21
Performance Comparison
  • IEEE 802.11

R
D1
Transmitter
C
A
Receiver
22
Analytical Model
  • Challenge MAC and channel are random processes
    with memory
  • Model relates physical-layer characteristics to
    MAC throughput
  • Time spent in contention
  • Markov model of modified IEEE 802.11
  • Average transmission rate
  • Due to channel distribution
  • Comparative model b/t multi-rate OAR and
    tractable systems
  • TIME OAR contends as often as single-rate IEEE
    802.11 with increased data per contention
  • PACKETS OAR reduces packet transmission time via
    per-contention rate adaptation

23
Simulation Results Under Ricean Fading
  • OAR has 42 to 56 gain over RBAR
  • Increase in gain as number of flows increases
  • Model predicts OAR RBAR throughput to within 7
    accuracy

24
Outline
  • TAP architecture
  • OAR an opportunistic auto-rate MAC
  • MOAR multi-channel OAR
  • Open problems

25
Multi-Channel Problem Formulation
  • Observe for two MUs, quality of different
    channels can have low correlation if
  • channel separation gtgt coherence bandwidth

26
Challenge
  • Ideal protocol is simple select the best channel
    at the instant of transmission
  • In practice, channel qualities are unknown
    a priori
  • Must first transmit and measure
  • Cost of measuring channels must be balanced with
    benefits of finding good ones

27
MOAR Protocol Sketch
  • Measure channel SNR at RTS/CTS handshake
  • If channel quality is high (above an SNR
    threshold), transmit via OAR
  • If channel quality is poor, skip to a new channel
  • next channel piggybacked in CTS
  • Design optimal stopping rule for skipping
  • stop when throughput gain of skipping to a better
    channel is outweighed by overhead
  • Ensure fairness

28
Optimal Stopping Rule Formulation
  • Let Xn denote the SNR of the nth measured channel
  • Let c denote the cost (in time) of measuring the
    channel
  • After observing Xn transmit or measure again?
  • cannot go back to previous channel (coherence
    time)
  • The reward for the nth selection is Xn-nc
  • after scaling SNR to rate and then to time
  • Objective maximize the expected reward
  • In a class of stopping rule problems (without
    recall)

29
Optimal Stopping Time
  • Let V denote the expected return from the
    optimal stopping rule
  • Suppose pay c and observe X1 x1
  • If continue, x1 is lost and c is paid
  • continuing, can obtain return V, but not more
  • start afresh
  • Optimal rule is threshold based
  • If xn lt V, continue if xn gt V stop
  • N minn ? 1 Xn ? V

30
Calculating the Stopping Threshold V
  • V E max(X1,V) c
  • F(x) represents the SNR distribution
  • Compute V
  • channel model and parameters (ex. K, d)
  • systems rate-SNR thresholds (ex. 1, 2, 5.5, 11)

31
MOAR Throughput Gains
  • Gains of 40-60 increasing with K and SNR
    variance
  • Ricean parameter K 0 is no line-of-sight signal

32
Effect of Node Distance
  • Greatest help when far away
  • Non-monotonic due to rate-SNR thresholds

33
Random Topologies
  • Nodes are uniform-randomly placed in a 250m
    circle
  • Optimal Skipping cheats looks at all channels
    (with no cost) and jumps to the best
  • Observe
  • MOAR extracts most available gain
  • close-by nodes detract from average gain

34
Outline
  • TAP architecture
  • OAR an opportunistic auto-rate MAC
  • MOAR multi-channel OAR
  • Open problems

35
DoS Resilience and Security
  • Old methodology
  • Design a network protocol
  • Optimize for performance
  • Discover DoS/Security holes
  • Ex. Route query floods
  • Patch one-by-one
  • Challenge
  • DoS-resilience and security as the foundation of
    network protocols
  • Recognize these issues are as important as
    performance

36
TAP Media Access and Scheduling
  • Challenge distributed scheduling
  • Others channel states, priority, backlog
    condition unknown
  • Ex. TAP As best recvr may be transmitting
    elsewhere
  • Ex. Traffic to be recvd may be higher priority
    than that to be sent
  • Traffic and system dynamics preclude scheduled
    cycles
  • Modulate aggressiveness according to overheard
    information

37
Multi-Destination Routing/Scheduling
  • Most data sources or sinks at a wire
  • Routing protocols for any wire abstraction
  • Scheduling
  • At fast time scales, which path is best
    (channels, contention, ) now?
  • Can delay/throughput gains be realized despite
    TCP?

38
Distributed Traffic Control
  • Distributed resource management how to throttle
    flows to their system-wide fair rate?
  • Throttle traffic near-the-wire to ensure
    fairness and high spatial reuse
  • TCP cannot achieve it (too slow and RTT biased)
  • Incorporate channel conditions as well as traffic
    demands

39
Capacity Driven Protocol DesignProtocol Driven
Capacity Analysis
  • Traditional view of network capacity assumes zero
    protocol overhead (no routing overhead,
    contention, etc.)
  • Protocols themselves require capacity
  • A new holistic system view the network is the
    channel
  • Incorporate overhead in discovering/measuring the
    resource
  • Explore capacity limits under real-world protocols

40
Problem Multiple APs/TAPs/within Radio Range
  • PHY Interference has disproportionate throughput
    degradation at MAC layer
  • Interference can lead to severe scaling
    limitations and starvation (worse than zero-sum
    game)

41
Summary
  • Transit Access Points
  • WiFi footprint is dismal
  • Removing wires is the key for economic viability
  • Opportunistic Scheduling (OAR/MOAR)
  • Exploit time and frequency diversity
  • Challenges
  • Multi-hop wireless architectures
  • Distributed control
  • Scalable protocols
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