wireless coexistence in open radio spectrum: curses and blessings guoliang xing assistant professor...

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

3

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

4

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?

6

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

9

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

11

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

12

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

13

14

Frame Adaptation

• Collision probability

• Sub-frame size optimizationCollision

Threshold

Maximum ZigBee frame size

ZigBee data rate250Kbps

Sub-Frame size

White space age

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 retx16

Outline




• 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

18

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

19

Spatial Coverage of AP

Coverage of 5 APs on the third floor of Engineering Building @ MSU

20

• 4 laptops at different locations for 2 days• Logging all beacon frames, traffic rate and etc.

Temporal Stability of Beacons

21

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

23

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

21

Outline




• 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


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


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


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


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




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

32

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


• Collaborative Sensing in Cyber-Physical Systems– Diffusion profiling using robotic sensors [IPSN12]– Volcano monitoring


38

• Commonly used for Smart Payment

• Limits the communication to a short range (10cm)

• Only supported by a few smartphone platforms

Near Field Communication (NFC)

39

• 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

41

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

wireless coexistence in open radio spectrum: curses and blessings guoliang xing assistant professor...

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