the use of pragma on distributed virtual instrumentation for signal analysis (divisa) domingo...
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The Use of PRAGMA on Distributed Virtual Instrumentation for Signal Analysis (DiVISA)
Domingo RodriguezWilson Rivera
ECE Department
University of Puerto Rico at MayaguezSeptember 24, 2007
Our Vision
Developing the concept of distributed virtual instrumentation for signal analysis (DiVISA) as a means of fostering interdisciplinary collaboration in signal-based information processing (SbIP) through the PRAGMA grid service community resource framework (GSCRF).
An Infrastructure for Human Collaboration
Applications Layer
Network Layer
Physical Layer
Physical WorldDistributed Sensor NetworksDSN
Medium Access ControlMAC
Service Oriented ArchitectureSOA
EnvironmentalObservatory
User’s TargetApplication
Observables
Signals
Data
Sensors Effectors
SignalProcessing
Information Processing
InformationKnowledgeProcessing
Knowledge
Decision System
Intelligence
PRAGMA: A Grid Service Community Resource Framework (GSCRF) for
Information Flow
“PRAGMA”
It deals with the gathering and processing of appropriate environmental information to aid in the process of effective decision making!
http://www.walsaip.uprm.edu
Environmental Surveillance* Monitoring (ESM)
*From French: sur- 'over' + veiller- 'watch'
ESM: WALSAIP’s Main Research Objective
WALSAIP: Wide Area Large Scale Automated Information Processing
Photo: Gail S Ross
Searching for the endangered Bufo
[Peltophryne] lemur through environmental surveillance monitoring
Aroma’s basin
Atolladora’s basin
Tamarindo’s basin
Picture: DRNA
Tamarindo’s basin
Master Sensor: gumstix embedded PC, Power supply for basic sensors, and remote internet access.
Basic sensors: gumstix embedded PC based acoustic recorders (frogloggers)
Ethernet and power cables
Environmental Surveillance Monitoring Region
WALSAIP Sensor Grid (WSG)
NS0
NS1
NS2
NSN-1
Basic Interface
Module (BIM)
Linear Sensor Array(LSA)
NSk: kth Sensor Node
EmbeddedComputer
System (ECSa)
Storage Device ~2TB
USA
China
Global users
ECS-G interface
Grid-S interface
Memory~2GB Grid Environment
Japan
Others
rth Master Sensor Node (MSN)
JBNERR, PR
The Concept of the Acoustical Map (A-MAP) Type I
Microphone Array
x
y
A-MAP processor
A-MAP Output Type I: Direction of Arrival (DoA)
x
y seagull_01
coqui_01
The Concept of the Acoustical Map (A-MAP) Type II
Sensor Array
x
y
A-MAP Processor
A-MAP Output Type II: Time-Frequency Distribution (TFD)
0.1 0.2 0.3 0.4 0.5 0.6 0.70
1000
2000
3000
4000
5000
6000
7000
Time
Frequency
0.05 0.1 0.15 0.2 0.25 0.3 0.350
1000
2000
3000
4000
5000
6000
7000Coqui Seagull
Analyzed sound
Full length sound
Analyzed sound
Full length sound
Signal Analysis Tools for Information Flow
Cohen-Class Type Time-frequency Distribution (TFD), C (t,f )
An example of distance measure between C1(t,f)=p1 and C2(t,f)=p2
Another example of distance measure: Kullback-Leibler Divergence
Rényi Divergence: Generalized Formulation of Kullback-Leibler Divergence
System Information Flow Characterization
Shannon entropy when applied to TFDs
The αth order Rényi entropy
Energy Flow Characterization: Power–Estimation in “energy change/unit time”
Information Flow Characterization: –Estimation in “entropy change/unit scale”
Raw Data Generation Requirements
Analyzing acoustic data to extract relevant information from a single site sensor array (M nodes) may be a “24/7/365” activity. At a 48K samples/sec rate, 16 bits A/D, single node raw data acquisition may generate about 5 Terabytes of data yearly. If a “single laptop” approach is taken for single node data analysis using existing software packages, it would take about four (4) person-year for a one (1) year raw data.
Advanced Computational Requirements
Large scale signal analysis techniques such as multivariate analysis and multispectral analysis of time-frequency distributions (TFD) bring orders of magnitude to initial raw data.
This work seeks to introduce automation techniques to large scale signal analysis by efficiently using distributed computing resources and
data on a grid infrastructure!
On Going Works
Developing a framework for automating large scale signal analysisIntegrating large scale signal analysis tools with a graphical user interface.Formulating a real time signal analysis framework for connecting to WSG testbeds.
Cyclic Short Time Fourier Transform (CSTFT)
CSTFT:
Virtual Sensor Grid Resource Infrastructure
iGIAB (INTEGRIDS Grid-in-a-Box)
Network-CentricSystem
iGIAB
More InteractionLess Interaction
iGIAB iGIAB iGIAB iGIAB
USGSServer
NWSServer
EPAServer
DRNAServer
(NOAA-JBNERRS)
Jobos NERRS Sensors(YSI 6600EDS,
WeatherStation, etc.)
DRNAServer
(Guanica Dry Forest Reserve)
UPRM-AIP Sensors(Xbow, Tmote,
Gumstix, Acoustics, etc.)
WALSAIPServer
Portal Host
Real-World Physical Signals
Operator Algebras Framework for Signal Analysis
2D Discrete Signal Spaces
One-Dimensional Discrete Finite Signals
)(2NZlx
Two-Dimensional Discrete Finite Signals
)(2, NNhx ZZla
One-Dimensional Signal Algebra
Operators
yxOx
ZlZlO
k
NNk
1
221 :
Time-Frequency Tools
hx
NNNN
ahxhx
ZZlZlZl
,
222
,,
:
Physical Signals
)(RLx
Sampling and Windowing
xyygg
ZlZlRL N
00
200
Two-Dimensional Signal Algebra
Operators baOa
ZZlZZlO
hxmhx
NNNNm
,2
,
222 :
1D and 2D Discrete Signal Spaces
Implementation on PRAGMA
Hardware Level
ProgrammingLevel
PRAGMACS 1
PRAGMACS 2
PRAGMACS N…
CS: Compute Site
C
MPI FFTW
C
MPI FFTW
C
MPI FFTW
NINF-G
G-FARM ApplicationLevel
LOCALCPUs
LOCALCPUs
LOCALCPUs
Application Development Tools
C
MPI
MPI
“Fastest Fourier Transform in the West.”
Ninf: A programming middleware which enables users to access resources on the Grid with an easy-to-use interface.
Gfarm File System: A next-generation network shared file system used as an infrastructure software.
PROGRAMMING TOOLS
SYSTEMRESOURCES
Conclusion and Future Works
Conclusion:The Concept of DiVISATime-Frequency Signal Analysis for Acoustical Environmental ApplicationsReal/Virtual Sensor Grid Resources PRAGMA as Community Resource
Future Works:Development of MPI-based Signal Analysis ApplicationsStudy Dynamic Behavior of PRAGMA Infrastructure for Signal-based Information Processing (SbIP).
QUESTIONS?