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Wireless Coexistence in Open Radio Spectrum: Curses and Blessings

Wireless Coexistence in Open Radio Spectrum: Curses and Blessings. Guoliang Xing Assistant Professor Department of Computer Science and Engineering Michigan State University. Outline. Wireless Coexistence in Open Radio Spectrum ZigBee link quality assurance [ICNP10, best paper award ]

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Wireless Coexistence in Open Radio Spectrum: Curses and Blessings

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  1. Wireless Coexistence in Open Radio Spectrum: Curses and Blessings Guoliang Xing Assistant Professor Department of Computer Science and Engineering Michigan State University

  2. Outline • Wireless Coexistence in Open Radio Spectrum • ZigBee link quality assurance [ICNP10, best paper award] • WiFi-assisted time sync [MobiCom10, RTSS11] • Collaborative Sensing in Cyber-Physical Systems • Diffusion profiling using robotic sensors [IPSN12] • Volcano monitoring [RTSS10] • Barcode Streaming for Smartphones [MobiSys 12]

  3. A Wireless Era • Today’s world is replete with wireless devices • 750 M laptops, 1 B smartphones, tablets, routers, remotes, baby monitors…. • Radios on same freq may generate interference • Frequency resources are getting scarce

  4. Crowded 2.4 GHz Spectrum • 2.4-2.5 GHz band is unlicensed • Wi-Fi, Bluetooth, ZigBee • Cordless phones, baby monitors, wireless headsets…. • Wi-Fi interference is a growing concern • 59 M Wi-Fi units in 2005, 409 M in 2009, 1 B in 2012

  5. ZigBee Technology • Low communication power (10~50 mw) • Application domains • Smart energy, healthcare IT, Industrial/home automation, remote controls, game consoles…. • Ex: >10 million smart meters installed in the US Industrial sensor networks (Intel fabrication plant) Smart thermostat (HAI ) Smart electricity meter (Elster)

  6. Co-existence of Wi-Fi and ZigBee • How bad (quantitatively) is the interference? • Do state-of-the-art link techniques suffice? • If not, how do we enable efficient co-existence? • Can we take advantage of the interference?

  7. Empirical Study of Coexistence WiFi interferer: 802.11g • Change WiFi node location • Measure ZigBeesending rate and packet delivery ratio Interference link Data link ZigBee sender and recver TelosB with CC2420 WiFi Interferer Position

  8. WiFi Hidden Terminals • Don’t trigger backoff at ZigBee sender • Corrupt packets at ZigBee receiver WiFi Interferer Position

  9. Wi-Fi Blind Terminals • Wi-Fi Interference on both ZigBee sender and receiver • Severe packet loss on ZigBee link • WiFi sending rate not significantly affected

  10. Why Blind Terminals ? ZigBee tx range ZigBee sender ZigBee recver WiFi interferer WiFi tx range • Power asymmetry • Heterogeneous PHY layers • WiFi only senses de-modulatable signals • Energy-based sensing? 10

  11. White Space in Real-life WiFi Traffic • Arrivals of Wi-Fi frames • Large amount of channel idle time white space: cluster gaps that can be utilized by ZigBee

  12. Modeling WiFi White Space • Length of white space follows iid Pareto distri. • Implementation • Collect white space samples in a moving time window • Generate model by Maximum Likelihood Estimation α = 1ms shorter intervals are not usable for ZigBee

  13. Basic Idea of WISE • Sender splits ZigBee frame into sub-frames • Fill the white space with sub-frames • Receiver assembles sub-frames into frame WiFi frame cluster ZigBee sub-frames ZigBee Time sampling window ZigBee frame pending

  14. Frame Adaptation • Collision probability • Sub-frame size optimization Sub-Frame size White space age ZigBee data rate 250Kbps Collision Threshold Maximum ZigBee frame size 14

  15. Experiment Setting • ZigBee configuration • TelosB with ZigBee-compliant CC2420 radios • Good link performance without WiFi interference • WiFi configuration • 802.11g netbooks with Atheros AR9285 chipset • D-ITG for realistic traffic generation • Baseline protocols • B-MAC and Opportunistic transmission (OppTx) • Evaluation metrics • Modeling accuracy, sampling frequency, delivery ratio, throughput, overhead 15

  16. Frame Delivery Ratio Unicast with 3 retx 16

  17. Outline • Wireless Coexistence in Open Radio Spectrum • ZigBee link quality assurance [ICNP10, best paper award] • WiFi-assisted time sync [MobiCom10, RTSS11] • Collaborative Sensing in Cyber-Physical Systems • Diffusion profiling using robotic sensors [IPSN12] • Volcano monitoring [RTSS10] • Barcode Streaming for Smartphones [MobiSys 12]

  18. Clock Sync in Sensor Networks • Fundamental service in sensor networks • A network-wide common notion of time • Essential for data ordering and processing • On-board clock suffers significant drift • Drift rate of crystal oscillator in TelosB is 30-50 ppm • Frequent synchronization is needed across network • Hardware-based solutions • GPS, WWVB • Cost, power consumption, poor coverage 18

  19. Key Idea • Wi-Fi access points broadcast periodic beacons • Sense beacons using ZigBee radio • Sampling wireless signals via Received Signal Strength (RSS) • Synchronize according to extracted beacons Periodic beacon signal TM 19

  20. Spatial Coverage of AP Coverage of 5 APs on the third floor of Engineering Building @ MSU 20

  21. Temporal Stability of Beacons • 4 laptops at different locations for 2 days • Logging all beacon frames, traffic rate and etc.

  22. Challenges • How to identify Wi-Fi beacons? • Many data frames between two beacons • Beacon period may be unknown!

  23. Finding Needle in a Haystack ZigBee radio ZigBee Sensor Beacon Detector Common Multiple Folding RSS Sampling & Shaping WiFi Access Point amplify periodic signals threshold 100

  24. Evaluation • 19 TelosB motes with TinyOS 2.1 • Sync to production Wi-Fi in MSU Engineering building • 10 continuous days of evaluation 21

  25. Outline • Wireless Coexistence in Open Radio Spectrum • ZigBee link quality assurance [ICNP10, best paper award] • WiFi-assisted time sync [MobiCom10, RTSS11] • Collaborative Sensing in Cyber-Physical Systems • Diffusion profiling using robotic sensors [IPSN12] • Volcano monitoring [RTSS10] • Barcode Streaming for Smartphones [MobiSys 12]

  26. Harmful Diffusion Processes Unocal oil spill Santa Barbara, CA, 1969 http://en.wikipedia.org BP oil spill, Gulf of Mexico, 2010 http://en.wikipedia.org Waste Pollution UK, 2009, Reuters • Diffusion profiling • source location, concentration, diffusion speed • high accuracy, short delay • Physical uncertainties • temporal evolution, sensor biases, environmental noises 04/19/2012 IPSN'12, Beijing, China 26

  27. Traditional Approaches Manual sampling labor intensive coarse spatiotemporal granularity Fixed buoyed sensors expensive, limited coverage, poor adaptability Mobile sensing via AUVs and sea gliders expensive (>$50K), bulky, heavy 04/19/2012 IPSN'12, Beijing, China 27

  28. Aquatic Sensing via Robotic Fish On-board sensing, control, and wireless comm. Low manufacturing cost: ~$200-$500 Limited power supply and sensing capability Smart Microsystems Lab, MSU 04/19/2012 IPSN'12, Beijing, China 28

  29. Problem Statement diffusion source robotic sensors • Maximize profiling accuracy w/ limited power supply • Collaborative sensing: source location, concentration, speed • Scheduling sensor movement to increase profiling accuracy 04/19/2012 IPSN'12, Beijing, China 29

  30. Overview of Our Approach Maximum likelihood based estimation New estimation accuracy metric Decouple sensors’ contributions New movement scheduling algorithm Near-optimal dynamic programming Evaluation based on real data traces 04/19/2012 IPSN'12, Beijing, China 30

  31. Outline • Wireless Coexistence in Open Radio Spectrum • ZigBee link quality assurance [ICNP10, best paper award] • WiFi-assisted time sync [MobiCom10, RTSS11] • Collaborative Sensing in Cyber-Physical Systems • Diffusion profiling using robotic sensors [IPSN12] • Volcano monitoring [RTSS10] • Barcode Streaming for Smartphones [MobiSys 12]

  32. Volcano Hazards • 7% world population live near active volcanoes • 20 - 30 explosive eruptions/year Eruptions in Iceland 2010 A week-long airspace closure [Wikipedia] Eruption in Chile, 6/4, 2011 $68 M instant damage, $2.4 B future relief. www.boston.com/bigpicture/2011/06/volcano_erupts_in_chile.html

  33. Volcano Monitoring • Seismic station • Expensive (~ $10K), bulky, difficult to install, up to a dozen of nodes for most active volcanoes! • Data collection and retrieval • ~10G data in a month • Processing • Detection, timing • 4D Tomography computation • Real-time, 3D fluid dynamics of a volcano conduit system • Extremely computation-intensive

  34. VolcanoSRI Project • Large-scale, long-term deployment • 100~500 nodes/volcano, 1-year lifetime • Collaborative in-network processing • Detection, timing, localization • 4D tomography computation • The tentative deployment map at Ecuador • (Photo credits: Prof. Jonathan Lees)

  35. Approach Overview system decision FFT • Select sensors with best signal qualities • FFT (computation-intensive) • Local detection • Decision fusion ‘1’ seismic sensor sensor selection ‘0’ decision fusion ‘1’ FFT FFT avoid raw data transmission

  36. Sensing Fidelity Verification IOIO board Amplifier Seismometer Geospace Geophone model GS-11D External GPS LG GT540 Android 1.6 GPS antenna

  37. Outline • Wireless Coexistence in Open Radio Spectrum • ZigBee link quality assurance [ICNP10, best paper award] • WiFi-assisted time sync [MobiCom10, RTSS11] • Collaborative Sensing in Cyber-Physical Systems • Diffusion profiling using robotic sensors [IPSN12] • Volcano monitoring • Barcode Streaming for Smartphones [MobiSys 12]

  38. Near Field Communication (NFC) • Commonly used for Smart Payment • Limits the communication to a short range (10cm) • Only supported by a few smartphone platforms

  39. COBRA System • Real-time visible light communication (VLC) system for off-the-shelfsmartphones • Sender encodes info into color barcodes • Barcodes are streamed (15 fps) from screen to camera • Receiver decodes barcodes to get info Streaming barcodes btw screen and camera sender receiver

  40. System Overview QR code

  41. Acknowledgement • Group members • TianHao (Ph.D, 2010-), Yu Wang (Ph.D, 2010-), Jun Huang (Ph.D, 2009-), Ruogu Zhou (Ph.D, 2009-), Dennis Philips (Ph.D, 2009-), Jinzhu Chen (Ph.D, 2010-), Mohammad-MahdiMoazzami (Ph.D, 2011-), Fatme El-Moukaddem (Ph.D, co-supervised with Dr. Eric Torng), Rui Tan (Postdoc) • Research Sponsorship (~1.5 M USD since 2009) • NSF CDI, VolcanoSRI, 2011-2015 (in collaboration with WenZhan Song @ GSU, Jonathan Lees@University of North Carolina, Chapel Hill) • NSF CAREER, performance-critical sensor networks, PI, 2010-2015. • NSF ECCS, aquatic sensor networks, PI, 2010-2013 • NSF CNS, Interference in crowded spectrum, MSU PI, 2009-2012 (in collaboration with Gang Zhou @ William & Mary) • Nokia University Cooperation Award

  42. MSU CSE Ranking • National Research Council's (NRC) 2011 • R-ranking 10%-25%, S-ranking 8%-35% of 126 • Overall 17% • Communications of the ACM • 17th of all US CSE graduate programs

  43. Representative Publications • Top conference publications since 2008 • RTSS (8), MobiCom (2), MobiSys (2), SenSys (1), IPSN (1), MobiHoc (1), ICNP (2), Infocom (3), ICDCS (2), PerCom (1) • Google Scholar: total # of citations since 2007: 2014, H-Index 20 • J. Huang, G. Xing, G. Zhou, R. Zhou, Beyond Co-existence: Exploiting WiFi White Space for ZigBee Performance Assurance, The 18th IEEE International Conference on Network Protocols (ICNP), 2010, acceptance ratio: 31/170 = 18.2%, Best Paper Award (1 out of 170 submissions). • R. Zhou, Y. Xiong, G. Xing, L. Sun, J. Ma, ZiFi: Wireless LAN Discovery via ZigBee Interference Signatures, The 16th Annual International Conference on Mobile Computing and Networking (MobiCom), acceptance ratio: 33/233=14.2%. • T. Hao, R. Zhou, G. Xing, M. Mutka, WizSync: Exploiting Wi-Fi Infrastructure for Clock Synchronization in Wireless Sensor Networks, IEEE Real-Time Systems Symposium (RTSS), 2011, acceptance ratio: 21%. • S. Liu, G. Xing, H. Zhang, J. Wang, J. Huang, M. Sha, L. Huang, Passive Interference Measurement in Wireless Sensor Networks, The 18th IEEE International Conference on Network Protocols (ICNP), acceptance ratio: 31/170 = 18.2%, Best Paper Candidate (6 out of 170 submissions). • R. Tan, G. Xing, J. Chen, W. Song, R. Huang, Quality-driven Volcanic Earthquake Detection using Wireless Sensor Networks, The 31st IEEE Real-Time Systems Symposium (RTSS), 2010. • J. Chen, R. Tan, G. Xing, X. Wang, X. Fu, Fidelity-Aware Utilization Control for Cyber-Physical Surveillance Systems, The 31st IEEE Real-Time Systems Symposium (RTSS), 2010. • X. Xu, L. Gu, J. Wang, G. Xing, Negotiate Power and Performance in the Reality of RFID Systems, The 8th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom), acceptance ratio: 27/227=12%, Best Paper Candidate (3 out of 227 submissions) .

  44. Challenge 1: Spatial Diversity • Complicated physical process • Highly dynamic magnitude • Dynamic source location Two earthquakes on Mt St Helens

  45. Challenge 2: Frequency Diversity • Responsive to P-wave within [1 Hz, 10 Hz] • Freq. spectrum changes with signal magnitude [1 Hz, 5 Hz] [5 Hz, 10 Hz] X 100 Signal energy: X 10000

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