1. Sybot: An Adaptive and Mobile Spectrum Survey System for WiFi Networks Kyu-Han Kim Deutsche Telekom R&D Lab USA Alexander W. Min and Kang G. Shin Real-Time Computing Lab, University of Michigan ACM MobiCom 2010 © Kyu-Han Kim

2. 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

3. 3 Outline  Limitations and Challenges  System Design  Performance Evaluation  Conclusion

4. 4 Limitations and Challenges  Exhaustive measurements  Comprehensive results [Raniwala03]  Easy to visualize and analyze data  Labor-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

5. 5 Outline  Challenges and Limitations  System Design  Performance Evaluation  Conclusion

6. 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 repeatability Efficiency and flexibility Adaptation and awareness

7. 7 App. layer  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 Mobility Controller MAP GUI Spectrum Monitor Filters       Sybot Operations  Metric of Interests - driver

8. 8  Comprehensive measurement  Cumulate n spectrum maps - Baseline spectrum map, B i  Selection of a grid size Complete Monitoring

9. 9  Cope with temporal variance  Identify areas with correlation  R, a set of reference grids b(1)={1,2} b(2)={1,2,4} b(3)={3,4} b(4)={2,3,4} b( i ) Reference grid Block {1,3} {1,2,3} {1,4} {2,3} Selective Monitoring 3 1 4 2 Candidate R

10. 10  Detect areas with deviation -  Update area w/ suspicious grids  Perform diagnostic movements Diagnostic Monitoring,

11. 11 Outline  Challenges and Limitations  System Design  Performance Evaluation  Conclusion

12. 12  Prototype  IEEE 802.11 Router (Linux)  iRobot Create for automation Performance Evaluation Wireless Router iRobot Sensors Sybot Prototype  Measurement and analysis  Corridors and office rooms  4 weeks and >10,000 points WiFi Test-bed

13. 13 Generating Repeatable Baseline Map  Complete monitoring result  Histogram of σ 87% of grids < 4 dBm

14. 14 Measurement space reduction > 50 % Reducing Space to Survey  Complete monitoring result  Selected reference grids

15. 15 Construction of a trade-off profile per site Building a Profile for Efficiency vs. Accuracy  Efficiency Profile  Accuracy Profile 70% reduction

16. 16 OBSTACLE Effectiveness of Diagnostic Monitoring Measurement space reduction > 56 %  Complete monitoring result  Diagnostic monitoring result

17. 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.

18. 18 Q&A Thank You Contact Information : kyu-han.kim@telekom.com