wireless coexistence in open radio spectrum: curses and blessings guoliang xing assistant professor...
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Wireless Coexistence in Open Radio Spectrum: Curses and Blessings
Guoliang Xing
Assistant ProfessorDepartment of Computer Science and Engineering
Michigan State University
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]
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
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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
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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
Smart thermostat (HAI ) Industrial sensor networks(Intel fabrication plant)
Smart electricity meter (Elster) 5
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?
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Empirical Study of Coexistence
• Change WiFi node location
• Measure ZigBee sending rate and packet delivery ratio
WiFi interferer:802.11g
ZigBee sender and recverTelosB with CC2420
Interferencelink
Data link
WiFi Interferer Position7
WiFi Hidden Terminals
• Don’t trigger backoff at ZigBee sender
• Corrupt packets at ZigBee receiver
WiFi Interferer Position8
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
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Why Blind Terminals ?
• Power asymmetry
• Heterogeneous PHY layers
– WiFi only senses de-modulatable signals
– Energy-based sensing?
ZigBee sender
ZigBee recver
WiFi interferer
WiFi tx range
ZigBee tx range
1010
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
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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
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Basic Idea of WISE• Sender splits ZigBee frame into sub-frames• Fill the white space with sub-frames• Receiver assembles sub-frames into frame
ZigBee
Time
WiFi frame cluster ZigBee sub-frames
ZigBee frame pending
sampling window
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Frame Adaptation
• Collision probability
• Sub-frame size optimizationCollision
Threshold
Maximum ZigBee frame size
ZigBee data rate250Kbps
Sub-Frame size
White space age
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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
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Frame Delivery Ratio
Unicast with 3 retx16
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]
• 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
Clock Sync in Sensor Networks
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Wi-Fi access points broadcast periodic beaconsSense beacons using ZigBee radio
• Sampling wireless signals via Received Signal Strength (RSS)Synchronize according to extracted beacons
Key Idea
Periodic beacon signal
TM
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Spatial Coverage of AP
Coverage of 5 APs on the third floor of Engineering Building @ MSU
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• 4 laptops at different locations for 2 days• Logging all beacon frames, traffic rate and etc.
Temporal Stability of Beacons
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Challenges• How to identify Wi-Fi beacons?
– Many data frames between two beacons– Beacon period may be unknown!
Finding Needle in a Haystack
RSS Sampling & Shaping
Common Multiple Folding
Beacon DetectorWiFi
Access Point
ZigBee radio
ZigBee Sensor
threshold
100
amplify periodic signals
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Evaluation 19 TelosB motes with TinyOS 2.1 Sync to production Wi-Fi in MSU Engineering building 10 continuous days of evaluation
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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]
• 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
Harmful Diffusion Processes
Unocal oil spillSanta Barbara, CA, 1969http://en.wikipedia.org
BP oil spill,Gulf of Mexico, 2010
http://en.wikipedia.org
Waste PollutionUK, 2009, Reuters
04/19/2012 IPSN'12, Beijing, China 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 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 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 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
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]
Volcano Hazards
• 7% world population live near active volcanoes• 20 - 30 explosive eruptions/year
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
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Eruptions in Iceland 2010A week-long airspace closure[Wikipedia]
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
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)
Approach Overview
• Select sensors with best signal qualities– FFT (computation-intensive)
• Local detection• Decision fusion
sensor selectiondecision fusion
system decision
FFTFFT
FFT
seismic sensor
‘1’
‘0’
‘1’
35 / 20
avoid raw data transmission
Sensing Fidelity Verification
SeismometerGeospace Geophone
model GS-11D
LG GT540Android 1.6
IOIO boardAmplifier
External GPS
GPS antenna
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]
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• Commonly used for Smart Payment
• Limits the communication to a short range (10cm)
• Only supported by a few smartphone platforms
Near Field Communication (NFC)
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• Real-time visible light communication (VLC) system for off-the-shelf smartphones- 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
COBRA System
System Overview
QR code
Acknowledgement • Group members
– Tian Hao (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-Mahdi Moazzami (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
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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
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) . 43
Challenge 1: Spatial Diversity
• Complicated physical process– Highly dynamic magnitude– Dynamic source location
Two earthquakes on Mt St Helens
44 / 20
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]Signal energy: X 10000 X 100
45 / 20