Sybot: An Adaptive and Mobile Sybot: An Adaptive and Mobile Spectrum Survey System Spectrum Survey System for WiFi Networksfor WiFi Networks
Kyu-Han Kim Deutsche Telekom R&D Lab USA
Alexander W. Min and Kang G. ShinReal-Time Computing Lab, University of Michigan
ACM MobiCom 2010 © Kyu-Han Kim
2
Why Spectrum Site-Survey for WiFi?
Coverage and capacity Interference or attack RF-based localization
Survey system for efficient and accurate monitoring
WiFi Spectrum Map
4
Limitations and Challenges
Exhaustive measurements Comprehensive results [Raniwala03] Easy to visualize and analyze dataLabor-intensive operation
Sensor-based measurements Continuous monitoring [Yin08] Can be inexpensive [Bahl05] Inflexible, due to its static location
Accuracy and repeatability Efficiency and flexibility Adaptation and awareness
6
Periodic and aperiodic surveys
Sybot: Spectrum Survey Robot
Design
Extraction of site-specific spectrum characteristics Controlling key survey parameters to meet requirements
Accuracy and repeatability Efficiency and flexibility Adaptation and awareness Decomposition of a survey task
Accuracy and repeatabilityEfficiency and flexibilityAdaptation and awareness
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App. layer
Periodic & on-demand Periodic & on-demand Adaptive monitoring
Periodic & on-demand Adaptive monitoring Grid-based spectrum map
Periodic & on-demand Adaptive monitoring Grid-based spectrum map Build/control a profile
Complete
Selective
Diagnostic
Scheduler
MobilityController MAP
GUI
SpectrumMonitor
Filters
Tmin
Thour
Tday Complete
Selective
Diagnostic
Sybot Operations
Metric of Interests -
-
m
jii jrss
m 1
)(1
m
jiii jrss
m 1
2))((1
driver
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APi
Unit grid
AP
Measurementpoint
APi
Good
Bad
Comprehensive measurement Cumulate n spectrum maps - Baseline spectrum map, Bi
Selection of a grid size
Complete MonitoringComplete
Selective
Diagnostic
9
AP
Measurementpoint
APi
Good
Bad
Cope with temporal variance Identify areas with correlation
R, a set of reference grids}|)()(|, and gridfor |{)( jijijib
b(1)={1,2}b(2)={1,2,4}b(3)={3,4}b(4)={2,3,4}
b(b(ii))
Reference grid Block
{1,3}
{1,2,3}
{1,4}
{2,3}
Selective MonitoringComplete
Selective
Diagnostic
3
1
4
2
Candidate RCandidate R
10
Detect areas with deviation - Update area w/ suspicious grids Perform diagnostic movements
AP
Measurementpoint
APi
Good
Bad
g1 g0
Suspicious reference grids
Diagnosticmovements
Diagnostic Monitoring
||)( iiidiff kidiff )(,
Complete
Selective
Diagnostic
12
Prototype IEEE 802.11 Router (Linux) iRobot Create for automation
Performance Evaluation
Wireless Router
iRobotSensors
Sybot Prototype
Measurement and analysis Corridors and office rooms 4 weeks and >10,000 points
WiFi Test-bed
13
Generating Repeatable Baseline Map
Complete monitoring result
Histogram of σ
87% of grids < 4 dBm
14
Measurement space reduction > 50 %
Reducing Space to Survey Complete monitoring result
Selected reference grids
15
Construction of a trade-off profile per site
Building a Profile for Efficiency vs. Accuracy
Efficiency Profile Accuracy Profile
70% reduction
}|)()(|, and gridfor |{)( jijijib
16
OBSTACLE
Effectiveness of Diagnostic Monitoring
Measurement space reduction > 56 %
Complete monitoring result
Diagnostic monitoring result
17
Conclusion
Spectrum site-survey for WiFi networks is important for key network management and services.
Key challenges and limitations in designing a spectrum survey system have been identified.
A prototype and extensive measurement study show its feasibility and effectiveness (> 50% reduction).
Sybot is a novel spectrum survey system that adaptively uses three complementary monitoring techniques.