lightening talks from globecom 2015

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Lightning Talk Sign Ups (Presenta4on slides submi:ed are green highlighted)

Timestamp Name Affiliation Email Title of talk Comments

12/5/15 22:57 Leonard Reder IEEE [email protected] Intro/Frequency Modulation in Foggy Mountain Breakdown

8/25/15 3:41 David Ramirez Rice University [email protected] "Why won't my funny video load?" asked my Mom.

9/10/15 13:55 David Pehlke Skyworks [email protected] UL Tx Diversity to Improve Cell Edge Performance, TRP, and SAR

9/18/15 11:47 Jean-Benoit Larouche Nutaq [email protected] Massive MIMO testbed Calibration 10/5/15 2:10 Haris Gacanin Alcatel-Lucent [email protected] Is design of 5G about customer experience?

10/6/15 1:28 Upkar Dhaliwal Future Wireless Technologies [email protected] Cognition MBRI: MANET scale-able Adhoc Mesh Communication

10/31/15 9:39 Mohamed-Slim Alouini KAUST [email protected] Vertical Backhaul/fronthaul for 5G 11/12/15 13:40 Molly Nicholas Qualcomm [email protected] Qbadge: A wearable networking platform

11/19/15 17:06 Dario Fertonani Phluido Inc. [email protected] Radio-as-a-Service 12/3/15 12:19 Piotr Pietrzyk Nutaq Innovation [email protected] The 5G puzzle: R&D Democratization

12/3/15 19:03 Rosa Zheng Missouri Univ of Science and Technology [email protected] Underwater wireless communications

12/4/15 5:43 Tristan Martin Nutaq Innovation [email protected] Connect The Next Billion

12/5/15 3:50 L. Dennis ShapiroRetired Chair/CEO Lifeline Systems [email protected] Designing for The Elderly

12/5/15 18:48 John Wang Mathworks [email protected] MATLAB and your wireless (5G) journey 9/9/15 5:22 Dr Oliver Holland King's College London [email protected] TV White Spaces in Europe Will be late! 12/6/15 9:09 Lei Zhang Plexxi, Inc [email protected] Plexxi - Simply a Better Network 12/7/15 0:16 Piotr Nutaq [email protected] The 5G puzzle: R&D Democratization

12/7/15 0:20 Mostafa El-Khamy Samsung Semiconductor, Inc. [email protected] Polar Codes Are OCBM Codes 12/7/15 1:33 Chunlin Yang Coleman University [email protected] Rich Communications Suite 12/7/15 1:45 Asaad Kaadan University of Oklahoma [email protected] Modular Optical Wireless Elements 12/7/15 15:28 Venkatesha Prasad TU Delft [email protected] Non-Sense! 12/7/15 17:39 Salih Safa Bacanli University of Central Florida [email protected] Encounter based Opportunistic Network Simulator

11/13/15 20:30 Narisa Chu CWLab Int'l [email protected] Technical Writing Skills for English-as-a-Second Language Engineers

[email protected] 2

Welcome to the Lightning Talks Session

Moderated by: Leonard J. Reder, JPL Former IEEE SFV Computer and Communica>ons Chapter Chair

Time Keeper: David Pehlke, Skyworks

GLOBECOM 2012 Lesson Learned!

2

“Goofy does not talk so he cannot do a lightning talk!” I asked…

[email protected]

Lightning Talk Session Lightning talks are short five minute talks on technical topics. Any

conference related subject can be presented (thoughts triggered by a presentation, a nifty algorithm trick, a thesis project, open source software project, company product, etc.). Rules:

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•  Everyone start talk with “My Name is …. And the title of my talk is….” •  Speaking slots assigned in order of sign up •  Each speaker is permitted five minutes to speak

–  Use from zero to three slides –  Please no animation on the slides –  Use of URLs within the presentations is encouraged

•  The five minute time limit on talks will be strictly enforced. Speakers should be prepared to present a concise talk

•  Email slides to [email protected] following the session, if you desire them to be posted on the conference web site

Frequency Modula/on in Foggy Mountain Breakdown

•  Foggy Mountain Breakdown is a bluegrass tune wriDen by Earl Scruggs and first recorded in 1949 –  It was background music in the 1967 moKon picture Bonnie and Clyde and various other shows

–  The most recognizable part of this tune is the slide on the fourth string, from first fret to the second forming the E minor cord, followed by slow backward roll

–  The slide effec+vely frequency modulates a note from D# to E crea+ng pronounced breaks within the tune

•  A MathemaKcal Analysis of this FM characterisKc of the Banjo can be found in: “String Stretching, Frequency Modula+on, Banjo Clang” by David Politzer, Caltech, hDp://www.its.caltech.edu/~politzer/FM.pdf

[email protected] 4

BANJO SOUND

A 5-‐STRING BANJO IS USUALLY TUNED TO D,B,G,D,G (294, 248, 196, 147, AND 393 Hz, RESPECTIVELY). THE BRIGHT SOUND HAS MANY HARMONICS.

SPECTRUM OF BANJO SOUND FOLLOWING A PLUCK OF THE OPEN 1ST STRING

BANJO WITH RESONATOR OFF AND ATTACHED

REFERENCES: “How a Banjo Works” J. Rae and T. Rossing, Proc. ISMA 2004. “Banjos” J. Rae (in Science of String Instruments ed. T. Rossing, Springer 2010) “The structural dynamics of the American five-‐string banjo” J. Dickey, JASA 114, 2958 (2003) “Experimental inves/ga/on of an American five-‐string banjo” L.Stephey and T. Moore, American Journal of Physics 124, 3276 (2008)

DEERING GOODTIME SPECIAL BANJO

What Limits LTE Cell Edge Performance?

Data rates reduces => drop in user experience is

very noticeable

UL Receive ≈ DL UL Transmit << DL

DL UL

0.25W

UE

UL Tx DL Rx

NF ~ 5dB

DL Tx

UL Rx

40W + NF ~ 3dB

eNodeB

Cell Edge Performance is More Important than Peak Data rates

Cell Edge Performance is Limited by UL Transmit Power

Proposed Use of UE UL Tx Diversity For Same Reason as Benefit to DL Rx

Dual Antenna Simultaneous Tx Transmission from UE Single Data Stream – Encoded According to Standard – Diversity Gain Why Higher Output Power Changes the Case for UE UL Tx Diversity

– Assumptions made during standardization : Total power of ALL Tx ≤ 23dBm – Higher Powers May Be Possible – and Provide Significant Benefit!

D.Pehlke, A. Raghavan , “Improving Cell Edge Performance with Novel Tx Path Enhancement”,

IWPC Workshop on Optimizing Mobile Device RF Performance Beyond LTE-A, 5/12/2015

Introduction of UL Tx Diversity as a Solution to the SAR Challenge

Simultaneous Transmission from Two UE Antennas can Deliver Potentially 3dB Higher TRP with Significantly Improved SAR • SAR is Localized in Hot Spots Around Antennas • Dual Antenna Tx Enables Spread of Total Power • Power is Doubled in Far Field at eNodeB

Benefits • Higher Power UL and Tx Diversity Both Add to

Address UL Limitations in LTE • Improved User Experience at Cell Edge • Larger Coverage Area to Avoid Dropped Calls, Improve UL SNR, and Extend High Data Rates

Higher Power and Lower SAR May Be

Possible with UE Tx Diversity

http://www.phluido.net/

http://www.phluido.net/

▪▪▪▪

Underwater Wireless Communications

Yahong Rosa Zheng

Department of Electrical & Computer Engineering

Missouri University of Science and Technology, Rolla, MO

(formerly University of Missouri-Rolla)

This work is supported by ONR and NSF

2

Why Underwater Wireless?

Titanic (figure from internet)

Why Underwater Wireless?

3

Ocean Exploration and Surveillance

Infrastructure Monitoring

In 1985, submarine

Argo discovered

Titanic at a depth of

12,000 feet (3657

meters). She used a

very long cable!

(figure from internet)

4

Possible communication means for

underwater

Optical beams: high BW, very short range ~ 20 m

Magneto-Inductive (MI): limited BW, short range

(100 meters)

Sound Propagation (Acoustic Communication):

Short range (<1 km): BW=100 kHz (HF)

Medium range (1-100 km): BW=10 - 25 kHz (MF)

BW= 30 - 40 kHz (HF)

Long range (1000 km): BW < 2 kHz (LF)

Underwater wireless communications:

a lot tougher and a lot more fun!

Have You Seen Dolphins Calling?

5

Knock, knock,

who is there?

Acoustic signals

recorded in SPACE08

experiment. Figures are

from WHOI

Tristan Martin Nutaq

Globecom 2015

www.nutaq.com

www.nuranwireless.com

NuRAN Wireless : Connect the Next Billion! Nutaq becomes part of Nuran Wireless

What Changes?

Everything !

Example: Connecting Rural Mexico

•  +20 villages connected so far •  136,000 remote villages without mobile connection...only in Mexico!

• 

• 

NuRAN Wireless : Connect the Next Billion! •  Two-thirds of the world do not have access to basic internet

•  NuRAN makes remote, low density areas profitable for mobile operators

•  Bringing accurate weather to farmers, online encyclopedia to kids in schools

We make a real difference. We impact people’s lives. Our Mission : NuRAN : Democratize the access to internet and voice networks in buildings,

offshore, and in rural locations Nutaq: Democratize the development of the technologies of tomorrow

NuRAN Wireless : Connect the Next Billion!

Together, let’s connect the next billion!

Thank you!

www.nutaq.com

www.nuranwireless.com

1© 2015 The MathWorks, Inc.

MATLAB for 5G Wireless Communications R&D---Globecom’15 Lightning Talk

John Wang, Ph.D.CES Industry ManagerCommunications, Electronics and Semiconductors [email protected]

mailto:[email protected]

2

Providing a Platform for Wireless R&D

3 Dimensions: MATLAB Environment for Algorithm and RF Modelling

– Invest your 5G efforts efficiently by building on top of existing functionality for Communications.

Re-use established algorithms, reference models, design and visualisation tools

Technology for Scalable Simulations

– Use the latest technology to scale the simulations, to get your simulation results more quickly.

Exploit parallel computing and GPUs without heavy investment in recoding.

Prototype and Deploy Algorithms to your chosen Hardware Platform

– Prototype and test your algorithms with realistic scenarios faster by interfacing MATLAB to

hardware, or deploying the algorithm to SDR platforms with code generation technology

3

Build Simulations in MATLAB… and Scale them Easily

Build 5G simulations with digital and RF building blocks

PHY algorithms and reference models: Communications System Toolbox LTE System Toolbox WLAN System Toolbox

RF Front-end, Beamforming: Phased Array System Toolbox Antenna Toolbox SimRF

Scalable Simulation• New MATLAB Execution Engine in R2015b

• up to 40% faster• Parallel Computing Toolbox & MATLAB

Distributed Computing Server• Distributed and Parallel Simulations• GPU Support

• MATLAB Coder• Convert MATLAB to C

4

Test with Hardware and Over-the-Air Signals

Test your algorithms with real signals and scenarios– Connectivity with instruments or SDR platforms– Deployment to SDR platforms, or to your own hardware

RF Signal Generator

Spectrum Analyzer

Zynq Radio SDR

USRP SDR

Use Supported Hardware…

…Or Your Own HardwareHDL Coder and Embedded Coder to implement your design on FPGA and DSP platformsEricsson paper: Radio Testbed Design Using HDL Coder:

http://www.mathworks.com/videos/radio-testbed-design-using-hdl-coder-92636.html

http://www.mathworks.co.uk/videos/radio-testbed-design-using-hdl-coder-92636.html

6

Find out more

If you want to find out more, come and talk to us

Visit mathworks.com/discovery/5g-wireless-technology.html

http://uk.mathworks.com/discovery/5g-wireless-technology.html

TV White Spaces in Europe

Oliver Holland, King’s College London, UK

IEEE Globecom 2015, Lightning TalksSan Diego, CA, USA, 8 December 2015

TV White Spaces in Europe, and the UK’s (Ofcom) TV White Spaces PilotUK s (Ofcom) TV White Spaces Pilot

Rules and device certification in Europe defined in “Harmonised Standard” developed by ETSI: ETSI EN 301 598developed by ETSI: ETSI EN 301 598.- 5 classes of white space devices’ ACLR performance.- Variable maximum EIRPs are given to devices by geolocation

databases Not fixed max power yes/no response from databasedatabases. Not fixed max power yes/no response from database.- These innovations make White Space available in very challenging

scenarios in Europe.

Major Pilot of TV White Space devices and framework has been ongoing in the UK, from June 2014 until end of 2015.

We have been leading one of the largest trials within this pilot.We have been leading one of the largest trials within this pilot.

Shown validity of the framework, and vast potential of TV White Spaces in a number of scenarios.

Examples of what can be achieved in London area in following slides.

Examples of Performance London M25 AreaExamples of Performance, London M25 Area

Examples of Performance London M25 Area

At l t 30 dB ll d EIRP

Examples of Performance, London M25 Area

F i l 20 dB At least 30 dBm allowed EIRP –“Mobile Broadband Downlink” scenario, Class 5, London M25 area. Number of usable channels

For comparison: at least 20 dBmallowed EIRP – “indoor Wireless Local Area Networking” scenario, Class 5, London M25 area. Number channelsLondon M25 area. Number channels


At least 30 dBm allowed EIRP – “Mobile Broadband Downlink” scenario,


,London M25

Number of channelsClass 1 Class 2 Class 3 Class 4 Class 5

Average 15.6 15.4 15.2 12.6 10.2STD 8.4 8.4 8.5 8.1 7.1CoV 0.54 0.55 0.56 0.64 0.70

At least 20 dBm allowed EIRP – “Indoor Wireless Local Area Networking” scenario, London M25

CoV 0.54 0.55 0.56 0.64 0.70

Number of channelsClass 1 Class 2 Class 3 Class 4 Class 5

Average 25.7 25.6 25.5 24.9 23.4STD 3 4 3 4 3 6 4 2 5 2STD 3.4 3.4 3.6 4.2 5.2CoV 0.13 0.13 0.14 0.17 0.22


CCDFs of available channels 1.0


for the London “M25” area: (a) macro-cell (downlink) scenario (>30 dBm EIRP), (b) indoor small cell scenario 0.5

0.60.70.80.9

CCDF

Class 5

Class 4

Class 3

Class 2

Cl 1(>20 dBm EIRP). Note, class 1 and 2 (and sometimes class 3) device results are often identical. 0.0

0.10.20.30.4

1 2 3 4 5 6 7 8 9 101112 1314 1516 171819 2021 2223 242526 2728 29C Class 1

1 2 3 4 5 6 7 8 9 101112 1314 1516 171819 2021 2223 242526 2728 29Number of channels

0 70.80.91.0

Class 5

Class 4

0.20.30.40.50.60.7

CCDF

Class 3

Class 2

Class 1

(a)

(b)0.00.10.2

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36Number of channels

(b)

AcknowledgementAcknowledgement

Some of the ideas in this presentation are supported by the ICT-SOLDER project, www.ict-solder.eu, FP7 contract number 619687, the ICT-ACROPOLIS Network of Excellence, www.ict-acropolis.eu., p

Also see E.g.,O. Holland, et al., “Some Initial Results and Observations from a Series of Trials within the Ofcom TV White Spaces Pilot” IEEE VTC 2015 Spring Glasgow UKwithin the Ofcom TV White Spaces Pilot , IEEE VTC 2015-Spring, Glasgow, UK, May 2015.O. Holland, et al., “TV white space in London, UK: availability and maximum achievable capacity”, Electronics Letters, Vol. 51, No. 12, May 2015.O. Holland, et al., “To White Space Or Not To White Space: That Is The Trial Within The Ofcom TV White Spaces Pilot”, IEEE DySPAN 2015, Stockholm, Sweden, September-October 2015.O Holland “White Space White Space Wherefore Art Thou White Space?”O. Holland, White Space, White Space, Wherefore Art Thou White Space? , IEEE TCCN Communications, December 2015.

BookBook A detailed coverage of aspects of TV white

spaces and other solutions for opportunistic spaces a d o e so u o s o oppo u s cspectrum sharing

O. Holland, H. Bogucka, A. Medeisis (Eds.), Opportunistic Spectrum Sharing and White Space Access: The Practical Reality, Wiley

Available now

26 h t i h d / ft 26 chapters covering hardware/software solutions, deployments and trials, mechanisms and algorithms, business, policy and market solutions, standards, deployment scenarios/applications etcscenarios/applications, etc.

http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118893743.html

12/9/2015© 2015 Plexxi, Inc. | Proprietary & Confidential |

Simply a Better Network.™

Simply a Better NetworkLei Zhang, Plexxi



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Modular Optical Wireless Elements (MOWE)

ASAAD KAADAN ([email protected]), University of Oklahoma, USA.

IEEE GLOBECOM 2015 LIGHTNING TALKS

Modules Array Frame Terminal


POLAR CODES ARE OCBM CODES

IEEE GLOBECOM, SAN DIEGO, CA, USA

MOSTAFA EL-KHAMY

MODEM SYSTEMS R&D, SAMSUNG ELECTRONICS

SAN DIEGO, CA 92121, USA

8 DEC, 2015

IEEE GLOBECOM 2015 Lightning Talk 2

12/10/201

5

M. El-Khamy , “Polar Codes are OCBM Codes”

OCBM Codes

Norbert Stolte introduced OCBM codes in his German 2002 PhD thesis, “Recursive Codes with the Plotkin-Construction and Their Decoding”, advised by Ulrich Sorger Started with binary 𝑢 𝑢 + 𝑣| Plotkin concatenation of binary outer codes

Considered BSC and AWGN channels Derived reliability of split channels ℎ(𝑢) an d ℎ(𝑣) which assume successive cancellation decoding

For AWGN channels, assuming split channels will also be Gaussian, the equivalent SNR is approximated using the sum-capacity observation 2 𝐶𝐵𝑃𝑆𝐾 = 𝐶ℎ

(𝑣)+ 𝐶ℎ

(𝑢)

Recursive Plotkin construction: each of the outer codes can be itself obtained from an 𝑢 𝑢 + 𝑣|

Maximize minimum Hamming distance of overall code for given dimension 𝑘: Dimension of outer codes is 1 on the 𝑘 rows of maximum Hamming weight, set other positions to

“1” ; construction includes Reed-Muller codes for certain k

Minimize word error probability under bit-wise multi-stage decoding With outer code dimension of 1 and equivalent SNR of bit-channels, WEP can be calculated

Optimized code for bitwise MSD (OCBM code): Select 𝑘 positions with smallest error probabilities 𝑃𝑒

(𝑖) to have dimension “1”, and set dimension of other positions to “0”

Bitwise multistage decoding complexity 𝑂(𝑁 log 𝑁) for code length 𝑁 = 2𝑚 Based on recursive decoding of Reed-Muller codes, Dumer, ACCC’00

List decoding with list size 𝐿 and complexity 𝑂(𝐿𝑁 log 𝑁) investigated and shown to be better than MSD as well as sequential (stack) decoding. Based on A* algorithm, previous work with Sorger ISITA’00, and later variations of decoding

metric by Dumer and Shabunov ISIT’01

Systematic encoding by identifying the set of independent positions in the code vector 𝒄 given the indices of the input information set, setting them to desired information bits, and then decoding Stolte also noted that systematic encoding gives better BER

OCBM, (32768,16384), AWGN,

n=15, decodings with different L


12/10/201

5


Polar Codes

Arikan proved that polar codes achieve the symmetric capacity of binary discrete memoryless channels, IT’09 Used recursive channel combining of identical copies of 𝑊:

Used channel splitting into good (𝑊+) and bad 𝑊− bit channels

Use Bhattacharyya Parameters (BPs) as a measure of reliability on a BMS BPs term coined by Kailath, TCOM’67, 0 ≤ 2 𝐸 𝑊 ≤ 𝑍 𝑊 ≤ 1

Recursive formulas for BPs are derived, which hold with equality if W is BEC

Code construction: For 𝑁, 𝑘 code select 𝑘 “good” bit-channels with smallest BPs to carry information

Freeze remaining “bad” bit-channels to zero

Encoding and Successive Cancellation Decoding complexities are 𝑂(𝑁 log 𝑁)

Arikan proved the Channel Polarization Theorem For any B-DMC, as 𝑁 → ∞, the fraction of good bit-channels approach the capacity 𝐼 𝑊

Systematic Encoding of Polar codes, Arikan, CommLett’11

Construction on AWGN Channels Gaussian Approximation and density evolution, Trifonov TCOM’12

Lower and upper bounds on bit-channel error probability using degrading and upgrading quantizations, Tal and Vardy, IT’13

Performance with SCD is not best at short length, ~1 dB gain by list decoding Tal-Vardy ISIT’11, Niu-Chen CommLett’12, Li-Shen-Tse CommLett’12

Relationship between Polar and Reed-Muller Code established Arikan, ITW’10; (Mondelli, Hassani, Urbanke), TCOM’14

𝑥 = 0, 0, 0, 𝑢3, 0, 𝑢5, 𝑢6, 𝑢7 𝐹⊗3


12/10/201

5


Numerical Comparison

AWGN Channel, 𝑁 = 2𝑛, 𝑅 = 1/2, non-systematic encoding

OCBM code construction with equivalent SNR calculation at each SNR

WER reproduced from Stolte’s thesis, Fig. 6.3

Polar code construction, two methods:

Genie-aided Successive Cancellation Decoding Monte-Carlo simulation

No Assumptions!

Numerical problems at higher SNRs, larger 𝑁

Gaussian Approximation with density evolution for longer codes

Polar codes are Optimized Codes for

Multistage decoding:

Polar codes are OCBM codes!

0 0.5 1 1.5 2 2.5 3 3.5 410

-6

10-5

10-4

10-3

10-2

10-1

100

Eb/N0 (dB)

Err

or R

ate

Polar vs OCBM, R=1/2, N=2n, AWGN

n=9, OCBM (Stolte) WERn=9, Polar (GA) WERn=9, Polar (GA) BERn=9, Polar (GSCD) WERn=9, Polar (GSCD) BERn=11, OCBM (Stolte) WERn=11, Polar WERn=11, Polar BERn=11, Polar (GSCD) WERn=11, Polar (GSCD) BERn=13, OCBM (Stolte) WERn=13, Polar WERn=13, Polar BER




http://ouwecad.github.io/MOWE/

Open source!!!


http://ouwecad.github.io/MOWE/

Get whatever is the best possible at the moment!!

http://homepage.tudelft.nl/w5p50/

12/9/2015

1

No Sense

Or

Non-Sense? Sensing without Sensors

Chayan Sarkar R. Venkatesha Prasad ([email protected])




12/9/2015

2

IoT and Energy

• What happens if one of the sensor becomes unavailable?




12/9/2015

3

Virtual Sensing Paradigm (VSP)

• Can the sensed value of the unavailable sensor be predicted?




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VSP: WHAT & WHY

• Predict sensing value of an unavailable sensor with the help of one/more correlated (neighboring) sensor(s).

• Save energy

• Estimate missing data (one/more) • Temporary replacement for faulty device • Less bandwidth consumption




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VSP Analogy

Guess/predict the next position – up/down?

sleeping node

active node

active node




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VSP Analogy

Guess/predict the next position – up/down?

sleeping node

active node

companion

Active Virtual Sensor (AVS)

Passive Virtual Sensor (PVS)

active node




12/9/2015

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VSP: HOW? AVS: a)sensor in sleep mode b)predict sensor data exploiting spatio-temporal correlation c)correlations are calculated using training data before sleep-mode d)significant energy savings.

PVS: a) suppress data transmission if data can be predicted based on

temporal correlation b) Some energy saving due to reduced transmission c) Help a AVS for accurate prediction (spatial correlation)




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Phases in Sensor Data Collection

• Complement sensors during operational period; X: Passive-VS, Y: Active-VS.




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Prediction Technique for AVS

• Hybrid of a transversal filter (for temporal prediction) and linear regression (spatial prediction).




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Mixing in right proportion

Y k[ ] =g ·ytem k[ ]+d·yspa k[ ]

spatial estimate

temporal estimate

final estimate




12/9/2015

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Real v/s Predicted Sensor Values

• Sensor data are collected from “Sensorscope: Lausanne Urban canopy deployment”




12/9/2015

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Prediction Error Variation

• Average prediction error for various operational period and revalidation period.




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Energy Consumption Comparison

• Combined energy consumption for two nodes using VSP and LMS-based scheme*.

* S. Santini and K. Romer. “An adaptive strategy for quality-based data reduction in wireless sensor networks”.




12/9/2015

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Is that it?

• Can two different types of sensors be correlated? • If yes, can we apply VSP on them?

• We have applied VSP on data collected from a light and a temperature sensor.




12/9/2015

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Heterogeneous Virtual Sensing

• Temperature sensor values are predicted using a light sensor as its companion.

See the plots carefully!




12/9/2015

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Multiple Neighbors




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Virtual Sensing – What Next?

Click here for a nice Video!


https://www.dropbox.com/s/jhozxh1sxtncy10/iltc_demo.mp4?dl=0






http://homepage.tudelft.nl/w5p50/ 12/9/2015

18

Optimization with VS

18

• Cluster sensors

based on virtual

sensing distance at

the CVO level.

• Representative

sensor from each

cluster, remaining

sensors are

replaced by virtual

sensor.




12/9/2015

19

Questions are Guaranteed in life; Answers ain’t.


EONS

Salih Safa BACANLI

https://github.com/cosai/EONS/

Open Source huh?



What is it? • Open source Wireless Network (discreet time) Simulator based on

encounter dataset

• Implemented in Java

• Research or some application purposes

• Documented and well commented

• Runs on command line

• Outputs

– Success Rates

– Message Delay

– Number of messages sent, received, added

– Hop Count

How to give the input?

• File input is checked and ping pong is tolerated.

• Number of messages and senders can be inputted.

• nodeid1 nodeid2 StartTimeinSeconds EndTimeinSeconds

1 3 45 67

3 7 56 60

23 56 120 1247

How to run that? • java -jar Simulator.jar tracefile.txt tts prob #ofnodes #ofmessages

#broadcasters alpha wantedprob isProphet lambda checkavg

timelimit

• Specify the parameters in parameters.bat/sh and run it many times

• Draw the graphs with some software (Matlab)

• To add your routing

– Write a class, override a method

– Change one line

• For more complicated stuff

– Write a class with your methods

– Change one line

Questions?

• Ephesus in Turkey (Ionian city)

lightening talks from globecom 2015

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