Transcript Document

GridCC: Real-time
Instrumentations Grids
A real-time interactive GRID to integrate
instruments, computational and information
resources widely spread on a fast WAN
Francesco Lelli
Istituto Nazionale di Fisica Nucleare
Laboratori Nazionali di Legnaro, Legnaro Italy
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Overview
• The GridCC Project: Introduction
• Bringing Instrument into the Grid: the
Instrument Element
•
•
•
•
Instrument Instrumentation
Fast Instrument Communication Channel
Standard Grid Interaction
Current Implementation performance analysis
• The GridCC Test-bed: Pilot application
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
General on the GridCC Project
• It is a 3 years project.
Started the 1st
September 04
• Funded by EU in the
Frame Program 6
• 10 Partners from 3 EU
Countries + (Israel)
• About 40 people
engagged
• www.gridcc.org
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Participant name
Country
Istituto Nazionale di Fisica Nucleare
Italy
Institute Of Accelerating Systems and
Applications
Greece
Brunel University
UK
Consorzio Interuniversitario per
Telecomunicazioni
Italy
Sincrotrone Trieste S.C.P.A
Italy
IBM (Haifa Research Lab)
Israel
Imperial College of Science,
Technology & Medicine
UK
Istituto di Metodologie per l’Analisi
ambientale – Consiglio Nazionale
delle Ricerche
Italy
Universita degli Studi di Udine
Italy
Greek Research and Technology
Network S.A.
Greece
The Grid Technologies to extend the
limit of a single computer (center)
Storage
Element
Computing
Element
Grid Gateway
Grid
Technologies
Computing
Element
User Interface
Computing
Element
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Extending the Grid Concepts
Grid Gateway
Terrestrial probes to monitor
The volcano activities
Satellite views
to monitor the volcano
Grid
Technologie
s
Control and Monitor Room
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
To model calculations
and disaster predictions
The GridCC Project
Instruments Grid
+
Computational Grid
GridCC Project
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrument Element: global scenario
Instrument
Instrument
Instrument
Element
Element
Element
Virtual
Virtual
Control
Control
Room
Room
Computing
Computing
Computing
Element
Element
Element
Web Service
Interface
Exec. WfMS
Service
WMS
User direct
Action
Indirect
Action
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Storage
Storage
Storage
Elements
Elements
Element
AgrS
Existing
Grid Infrastructures
The GridCC Architecture
Virtual
Control Room
(VCR)
All end user
access is via
Collaborative
the VCR
The IE is a
Services
(CS)
Users generally
virtualization of
not working alone
Information
the real physical
and Monitoring “Fast” all pervasive
instrument
Services
messaging system
Direct access to IE
(IMS)
Instrument
SE (and
CE) Services
possible
elements
Execution
Information
Instrument
System
Slowly updating
but often not desirable
(IE)
elements
(IS)
Compute information
and
Of course
Instrument
(IE)
Storage Elements
there may be
SecurityOf
is course
elements
Watching
More
complex
(via
the
IMS)
(with advanced
many IEs
essentialMany
to CEs
Security
(IE)
for
workflows,
problems
anywhere
Services
reservation) the success
of
and SEs
in the
including
systemadvanced
and
the project
acting
reservation
to resolve
and
them.
QoS
Compute
Storage
guarantees , allowed
element
Virtual
Control Room
(VCR)
Element
(SE)
Storage
(CE)
Element
(SE)
Compute
element
(CE)
Storage
Element
(SE)
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Global Problem
Solver
Compute
element
(CE)
IE Requirements
Web Services
Storage
Element
Computing
Element
Instrument Element
Any Protocol or
physical connection
Sensor
Instrument
Network
Instrument
Computing
Element
D
F
A
Instrument
Element
1: Provide a uniform access to the physical
device
W
E
Grid
C
B
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
2: Allow a standard grid access to the
instruments
3: Allow the cooperation between different
instruments that belong to different VOs
Instrument Element: a Black Box
Quick Answers to the previous slide:
1) The VIGS provide the a uniform
instrument instrumentation way
2) The fast communication channel
Grid
disseminate the acquired information
Interaction
between instruments
3) The Data Mover provide a standard Grid
Interface in order to be accessed by
others Grids components like the SE
and the CE
Instrumentation
Instruments
IE
Data Mover
Instrument
VIGS
Fast communication channel
• The term Instrument Element describes a set of services that provide the needed
interface and implementation that enables the remote control and monitoring of
physical instruments.
IE Key Developers: E. Frizziero1, M. Gulmini1,3, F. Lelli1,2 ,G. Maron1,A.
Oh3, A. Petrucci1, S. Squizzato1, S. Traldi1
1 Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Legnaro
2 Dipartimento di Informatica, Università Ca’ Foscari di Venezia
3 CERN European Organization for Nuclear Research
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrument Instrumentation
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Device Virtualization Model
1.
2.
3.
4.
Instrument
Parameters
Parameters hold configuration information
Attributes hold instrument variables
Control Model hold actions
XML Based Language to allow the device to describe itself
Attributes
Control
Voltmeter
Model
XML Based
Language
• Parameters: Maximum Voltage, Minimum voltage
• Attributes: measured Voltage
• Commands: Perform a measure
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrument Instrumentation
lockInstruments
unlokInstruments
retrieveLoked
getIstance
get/Set Parameters
getCommands
executeCommand
getState
getStateMachine
VIGS
getContexts
getInstrumentManagers
getInfo
IE
Instruments
Crucial non-Functional
Requirements:
• Instruments could be order of 106
• Only authorized people should
access to the instruments of a VO
• The instrumentation is not a batch
process like a job submission!
Interactivity is mandatory
getRemoteExecutionTime
getOneWayCost
getTotalMethodExecutionTime
• A Distribute and hierarchic
implementation is mandatory
• the Security overhead should be
negligible
We can divide the Instrumentation in 3 main parts:
• The direct access to the Instruments
• The advance instrument reservation (interaction with the
Agreement Service (AS)) in order to achieve (hard) guarantees
• The Possibility to predict the execution time of the instrumentation
methods in a concurrent access (soft guarantees)
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrumentation method Documentation
http://sadgw.lnl.infn.it:2002/IEFacade
Instrument Element Architecture
create()
destroy()
execute()
getState()
Access Control Manager
Virtual Instrument Grid Service (VIGS)
Instrument Element
Inf & Mon
Service
Resource
Service
Instrument
Manager
Problem
Solver
• The term Instrument Element
describes a set of services that
provide the needed interface and
implementation that enables the
remote control and monitoring of
physical instruments.
Data
Mover
Data Flow
State Flow
Error Flow
Monitor Flow
Control Flow
Data
Collector
IMS
Proxy
Control
Manager
Real Instruments
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Control Manager
Event
Processor
FSM
Engine
Input
Manager
Resource
Proxy
Access Control Manager
Instrument Element Implementations
Instrument Element
Resource
Service
Inf & Mon
Service
Instrument
Manager
Problem
Solver
Data
Mover
The IE components are typically implemented into a fully
equipped Machines (e.g. dual core cpus, large memory, large disks, etc).
This is true for RS, IMS and PS. For IM (and DM) there are 2 possibilities,
according to the application type:
• IM implemented in a fully equipped machine
• IM embedded into the instrument that should be controlled
IMS
RS
IM
Embedded Web Service
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrument Manager
Instrument Manager
Customizable
Control Manager
Event
Processor
FSM
Engine
Input
Manager
Resource
Proxy
IMS
Proxy
Plug-in modules to interface to the instrumen
Data
Collector
Data Flow
Monitor Flow
State Flow
Control Flow
Error Flow
Instruments
IM is composed by 3 main components:
- Control Manager:
- Input Manager. It handles all the input events of the IM. These includes commands from GU
errors/state/log/monitor messages.
- Event Processor. It handles all the incoming message and decide where to send them. It ha
- FSM. A finite state machine is implemented
- Resource Proxy. It handles all the outgoing connections with the resources.
- Data Collector. It get data from the controlled instruments and make them available to the data mover. A
is even foreseen.
- IMS Proxy. It receives error/state/log/monitor information from the controlled resources and forward them
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Partition/Configuration
retrieve methods
Partition and Lock
setting methods
•
•
•
•
•
•
•
Discovery
Manager
Subscribe
Manager
Configuration
setting methods
Partition&Lock
Discovery
methods
Configuration
Manager
Available
Resources
Partition
Definitions
Manager
Configuration
Definitions
RS Data Bases
Resource Service Architecture
The Resource Service (RS) handles all the resources of an IE and manages
their partition (if any).
A resource can be any hardware or software component involved in the IE
(instruments, Instrument Managers, IMS components)
RS stores the configuration data of the resources and download them to
resource target when necessary
Resources can be discovered, allocated and queried.
It is the responsibility of the RS to check resource availability and contention
with other active partitions when a resource is allocated for use.
A periodic scan of the registered resources keeps the configuration database up
to date.
RS is interfaced to the WMS
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
•
Instruments
The Information and Monitor Service (IMS) collects messages and monitor data coming
from GRID resources and supporting services and stores them in a database. There are
several types of messages collected from the sub-systems. The messages are catalogued
according to their type, severity level and timestamp. Data can be provided in numeric
formats, histograms, tables and other forms.
The IMS collects and organizes the incoming information in a database and publishes it to
subscribers. These subscribers can register for specific messages categorized by a number
of selection criteria, such as timestamp, information source and severity level.
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instruments
Instruments
Instrument
Manager
•
Instrument
Manager
SUBSCRIBERS
Errors
Log info
Monitor
State
PUBLISHERS
(Instruments nodes)
Instrument
Manager
Information and Monitor System
(IMS)
Problem Solver
Step 3 On-line information can be
analyzed in order to detect possible
malfunctions
Problem Solver
On Line
Analisys
Pub/Sub
Step 1 The control manager can
perform an autonomous recovery
action where the cost for the
determination it is not so heavy .
Instrument Manager
IMS
Proxy
Data Mining
Tools
Control
Manager
DB
Algorithms evaluations :
State Flow
Error Flow
Monitor Flow
Instrument Manager
Rule Induction, Tree,
Functions, Lazy, Clusters and
Associative
IMS
Proxy
Control
Manager
Instrument Manager
IMS
Proxy
Control
Manager
100.00%
90.00%
80.00%
accuracy
70.00%
Average Rule Accuracy
60.00%
Average Tree Accuracy
Average Function Accuracy
Average Instance Accuracy
Average Cluster Accuracy
50.00%
40.00%
30.00%
20.00%
10.00%
connect-4
krkopt
Shuttle(1)
Shuttle(2)
LetterRecognition
mushroom
Page-Blocks
Sick-euthyroid
Segment
Segmentation
tic-tac-toe
Pima-Indians-Diabetes
Breast Cancer Wisconsin
housing
balance-scale
bupa
voting-records
breast cancer
iris
glass
0.00%
dataset
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Step 2 Persistent information can be
analyzed in order to extract
knowledge
Instrument Manager
IMS
Proxy
Control
Manager
Poviding QoS over Web Sevices
Performing a remote method Invocation in a given amount of time:
t0
t8
Processing
t7
Serialization
Deserialization
Client side
Crucial Times are:
t3-t0 One Way Cost
•
•
t1
t6
Transmission
Transmission
t2
t5
Deserialization
Serialization
Network
t4-t0 Remote Execution Cost
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
t4
Service side
t7-t0 Total Method Execution Cost
Avg =f(Cpu, Inputsize, Outputsize, Algorithm, Key-Factor, net)
SDev =F(Cpu, Inputsize, Outputsize, Algorithm, Key-Factor, net)
Cpu = machine HD + machine load (client and server side)
Algorithm = method semantic
Net = bandwidth + RTT
Key-Factor = input value that change the method semantic
Inputsize, Outputsize =effective type and dimension
t3
Operation
execution
Virtualization of Real devices
Each IM Represent the virtualization of a device
Web Cam Position
Max Value min Value
Video Streaming
linked
Temperature
Unlinked
linked
IE
create()
IM Cam
IM Sensor
destroy()
Data for Model
Calculations
execute()
getState()
Resource
Service
Inf & Mon
Service
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Data
Mover
Predictions
Unlinked
Virtualization of Real devices (I)
Each IM Represent the virtualization of a device
Web Cam Position
Max Value min Value
Video Streaming
linked
Temperature
Unlinked
IE
linked
IM Cam
IM Sensor
create()
destroy()
IM Master Controller
execute()
getState()
Resource
Service
Inf & Mon
Service
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Data for Model
Calculations
Data
Mover
Predictions
Unlinked
Virtualization of Real devices (II)
Web Cam Position
Video Streaming
Max Value min Value
Temperature
linked
Unlinked
linked
IM Cam
RS
IMS
IE Cam
Data
Mover
IE Sensor
IMSensor
Each Instrument is virtualized
and a 3° IE use this others IE
in order to accomplish a complex
functionality
IM Master
Controller
RS
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
IMS
RS
IMS
IE Master
Data
Mover
Data
Mover
Data for Model
Calculations
Predictions
Unlinked
Virtualization of Real devices (III)
Web Cam Position
Max Value min Value
Video Streaming
linked
Temperature
Unlinked
IE
linked
Sensor Proxy
create()
Cam Proxy
destroy()
IM Master Controller
Data for Model
Calculations
execute()
getState()
Resource
Service
Inf & Mon
Service
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Data
Mover
Predictions
Unlinked
Fast Instrument Communication
Channel
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Message Oriented Middleware
•
Topic A
•
Topic B
•
Subscribers Subscribe to a
given Topic/Queue with a
subscribe condition
Publisher publish message in
asynchronous in a given
Topic/Queue way with a given
message condition
Publisher and subscribers can
be part of the same program or
in WAN distributed machines
Queue Q
•
In Our Case:
• Each instrument can be a data
publisher or a data consumer
• For more demanding
application an instrument must
send/receive data in a
streaming way
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
•
JMS Provide a standard set of
API that standardize this
communication system
Many Commercial and
academic implementation of this
API exist in both C/C++ and
Java (NaradaBrokering, Sun,
IBM, SonicMQ etc etc )
RMM-JMS
•
•
•
•
•
•
RMM-JMS is a JMS implementation on top of our high performance Reliable
Multicast Messaging (RMM) layer which provides one-to-one, one-to-many
data delivery or many-to-many data exchange, in a message-oriented
middleware point-to-point or publish/subscribe fashion
The exceptional performance supports remote and distributed control and
operation of scientific instruments such as sensors and probes
Multicast transport for publish/subscribe messaging: Supporting the JMS
Topic-based messaging and API, with matching done at the IP multicast level.
The transport is a Nack-based reliable multicast protocol.
Direct (broker- less) unicast for point-to-point messaging: JMS Queues are
implemented over RMM queues. The transport is the TCP protocol.
Brokered unicast transport for publish/subscribe messaging. The broker
receives messages from the producer in either unicast or multicast delivery
mode, and sends the messages to the subscribers in either mode
broker serves as a bridge in a LAN-WAN-LAN configuration
Main Contribution of IBM Haifa Research Lab (Israel)
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Performance: message rate – the many-to-one
• Blade center with 12 CPUs and 1GB Ethernet switch
• No message loss
• Total throughput: 61MBytes/sec. and 67MBytes/sec. for
(a) and (b) respectively
(a) rate - msg size 1000 bytes
(b) rate - msg size 100000 bytes
90000
900
80000
800
70000
700
min
60000
Max
50000
Avg
40000
SDev
msg/sec
1000
msg/sec
100000
600
500
400
30000
300
20000
200
10000
100
0
min
Max
Avg
SDev
0
0
5
10
15
Number of Publishers
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
20
0
5
10
15
Number of Publishers
20
Performance: message rate – the one-to-many
• Blade center with 12 CPUs and 1GB Ethernet switch
• No message loss
• Peak result of over than 400000 msg/sec. was reached
Rate, msg size 1 Byte
Rate, msg size 1000 bytes
600000
90000
80000
500000
70000
msg/sec
msg/sec
400000
300000
60000
min
min
50000
Max
Max
Avg
40000
Avg
SDev
SDev
30000
200000
20000
10000
100000
0
0
0
0
5
10
15
20
25
Number of Subscribers
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
30
5
10
15
20
25
Number of Subscribers
30
Performance: round trip time (RTT, Latency)
• Two machines with a single publisher and a single subscriber on each one
• Average round trip time computed over 1000 samples
RTT
100
Time (mSec)
10
Avg
Sdev
Ping
1
0.1
0.01
1
10
100
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
1000
10000
Messages Size
100000
1000000
Standard Grid Interaction
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Data Mover
IE
Instrument Resources
Data
Mover
Data
Data
Collector
Data
Collector
Collector
IM
Web Service Interface: get_data()
SRM interface
Http Server and
TCP/IP raw socket
IM
IM
•
•
•
The task of this element is to get data from the “data collector” of the IM
Data can be accessed via:
– Web service interface for generic data dump (e.g. slow storage, spy
stream, etc.)
– grid storage element (SE) and available CEs can access to the
data via an SRM Interface
– Http server and TCP communication for high performance had-hoc
data transfer
The Data Mover exposes its methods to the IE web service and can be
instrumented itself as an instrument.
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Current IE Implementation
a fist taste
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrument Manager Performances (I)
Instrument Manager Invocations
execute()
getState()
Test 1
Data
Collector
IMS
Proxy
Event
Processor
FSM
Engine
Input
Manager
Resource
Proxy
Average
40
min
30
Max
20
Variance
10
0
1
HTTP Transport Layer
Asyncronous msg Rate
Test 1: Web Service invocation
and status switch of FSM
Test 2: Soap Server receiving
XML message format. DOM
based parser
Control Manager
50
Test 2
250
Messages per Second
destroy()
Access Control Manager
create()
Invocation per Second
60
Virtual Instrument Grid Service (VIGS)
200
Average
150
min
100
Max
Variance
50
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15
Number of Client
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Instrument Manager Performances (II)
Command Distribution Time
1
1+2
4.5
2
Average Time (sec)
4
3.5
1FM
3
1FM M
2.5
3FM
3FM M
2
3FM 3PC
1.5
3FM 3PC M
1
0.5
0
10
IM with CMS Instruments
50
80
120
3
Number of Instrument
1
3
1
3
Optimized environment
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
JMS increasing the subscribers number
Summary Mysql vs Oracle
700
2500
600
500
msg/sec
msg/sec
2000
Oracle 100
1500
Oracle 1
Mysql 100
1000
400
w ith selector
field
300
w ithout
selector field
200
Mysql 1
100
500
0
0
0
0
2
4
6
8
10
12 14
16
18 20
2
4
22
6
8
10
12
n subscriber clients
n publisher clients
DB
Pub/Sub
(JMS)
TCP/IP
IMS
Performances
Web
Service
Interface
IMS
IMS
Proxy
….
IMS
Proxy
Summary Test output disabled
Summary Java vs Xdaq( C++) 1 socket output
8000
IMS
Proxy
3500
msg/sec
3000
2500
java
2000
xdaq
1500
Errors/log/states messages
(xml and java objs)
7000
6000
msg/sec
4000
xdaq
5000
4000
java
3000
c++ (not xdaq)
2000
1000
1000
500
0
java-C++
contemporary
0
0
0
2
4
6
8
10
12
14
16
18
20
22
n publisher clients
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
2
4
6
8
10
12
14
n publisher clients
16
18
20
22
Main IE Pilot Applications:
Power Grid
Virtual
Virtual
Control
Control
Room
Room
Instrument
Manager
Power Grid
V.O
Gas
..
.
Instrument
Element
Sola
r
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Main GridCC Pilot Applications:
Control and Monitor of high energy experiments
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Main GridCC Pilot Applications:
Control and Monitor of high energy experiments
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
The CMS Data Acquisition
2 107 electronics channels
40 MHz
• O(104 ) distributed
Objects to
– control
– configure
– monitor
• On-line
diagnostics and
problem solving
capability
• Highly interactive
system (human
reaction time fraction of second)
100 Hz
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
• World Wide
distributed monitor
and control
CMS Prototype
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
CMS Prototype: IEs at work
CMS Instrument Elements
- GridCC middleware used for CMS
MTCC (Magnet Test and Cosmic
Challenge)
TOP
Det 1
Det 11
Det
Detector
GTPe
- 11 Instrument Elements with a
hierarchical topology
- Instruments are in these case Linux
hosts where the cms on-line software
is running
8
1
DAQ
DAQ IE Instrument Managers
DAQ
- More than 100 controlled hosts
Trigger
- 25 days to the start of the data taking !
TTS
FilterFarm
FedBuilder
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
RuBuilder
IDS Intrusion Detection System
1. Taking
Control
Pirated machines
Domain A
Target
domain
"zombies"
X
Pirated machines
Domain B
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
IDS Intrusion Detection System
A DDoS Attack Domain-wise
Sources
of the attack
Sensor
Instrument
Element
Sensor
Instrument
Element
Sensor
Instrument
Element
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Sensor
Instrument
Element
Sensor
Instrument
Element
Target Domain
Main GridCC Pilot Applications:
Remote Operation of an Accelerator
Elettra Synchrotron
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
The other GridCC pilot applications
• Meteorology (Ensemble Limited Area
Forecasting)
• Device Farm for the Support of Cooperative
Distributed Measurements in
Telecommunications and Networking
Laboratories
• Geo-hazards: Remote Operation of
Geophysical Monitoring Network (see first
slides)
• Medical Devices need a close loop between
the data acquisition and the output result
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Conclusion
• The GridCC project is integrating instrument into
traditional computational/storage Grids.
• IEs need an high interaction and interactivity
between itself and the users.
• The GridCC IE implementation is currently
installed in heterogeneous applications
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Question?
• Thx for your time
More information: www.gridcc.org
On-line Demo at: http://sadgw.lnl.infn.it:2002/IEFacade
Acknowledgement:
The GridCC project is supported under
EU FP6 contract 511382.
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Another GridCC applications:
Migraine Attacks Treatments
EEC
1. Data taking
2. Data Processing
GRID
3. Result Visualization
and control
1 minute loop
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
4. Action
The control of the CMS Data Acquisition
Storage
Element
Virtual
Cntr. Room
Drift Tube
CMS Subdetector
Supporting
Services
Diagnostics
Virtual
Cntr. Room
• Acquire data from a
CMS Muon chamber
• Move data to a Storage Element
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Computing
Element
• Submit an analysis job
• Retrieve the job result
The control of the CMS Data Acquisition
Legnaro
Data Flow
Virtual Instrument Grid Service (VIGS)
create()
destroy()
execute()
getState()
ISCHIA
Access Control Manager
CMS
Control
Structure
Instrument Element
Inf & Mon
Service
Resource
Service
Instrument
Manager
Problem
Solver
Data
Mover
State Flow
Error Flow
Monitor Flow
Control Flow
Web Service
Interface
Web Service
Comunication
Retrieve the Configuration
Data
Collector
IMS
Proxy
Control
Manager
Control Manager
Event
Processor
FSM
Engine
Input
Manager
Resource
Proxy
Run Control
Real Instruments
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
A New Messages Oriented Middleware
RMM-JMS broker/bridge
client
client
RMM-JMS
RMM-JMS
RMM
RMM
RMM-BRG
RMM
RMM
RMM-BRG
RMM
RMM
RMM-JMS
RMM-JMS
client
client
LAN domain
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
LAN domain
General on the GridCC Project
• It is a 3 years project.
Started the 1st
September 04
• Funded by EU in the
Frame Program 6
• 10 Partners from 3 EU
Countries + (Israel)
• About 40 people
engagged
• www.gridcc.org
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Participant name
Country
Istituto Nazionale di Fisica Nucleare
Italy
Institute Of Accelerating Systems and
Applications
Greece
Brunel University
UK
Consorzio Interuniversitario per
Telecomunicazioni
Italy
Sincrotrone Trieste S.C.P.A
Italy
IBM (Haifa Research Lab)
Israel
Imperial College of Science,
Technology & Medicine
UK
Istituto di Metodologie per l’Analisi
ambientale – Consiglio Nazionale
delle Ricerche
Italy
Universita degli Studi di Udine
Italy
Greek Research and Technology
Network S.A.
Greece
GridCC Main Architecture
SecurityAutS
Service
Instrument
Instrument
Instrument
Element
Element
Element
TGS
PolR
Computing
Computing
Computing
Element
Element
Element
Virtual
Virtual
Control
Control
Room
Room
Web Service
Interface
Storage
Storage
Storage
Elements
Elements
Element
Exec. WfMS
Service
WMS
AgrS
User direct
Action
Indirect
Action
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
Global
Problem
Solver
Existing
Grid Infrastructures
Instrument Element Facade
Virtual Instrument Grid Service (VIGS)
moveToSE
read
submitJob
Logs, Errors, States, Monitors
IMS
IM
IM
IM
Commands
Status, Parameters
Data Mover
Grid Operations
IE
GridFTP
MoveData
Grid Operations
getIstance
get/Set Parameters
getCommands
executeCommand
getState
getStateMachine
RS
Instrument
Element
VIGS
getContexts
getInstrumentManagers
getInfo
Submit
Job to
Grid
Fast
Output
Channel
IMS
Subscribe
(JMS)
DB
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
• The term Instrument Element
describes a set of services that
provide the needed
interface and implementation that
enables the remote control and
monitoring of physical instruments.
Interacting with Instrument Elements
1) Full GridCC Environment
VCR
2) Partial GridCC Environment
GPS
This mode of operation can be used
when the application does not need
to access CEs and SEs. It coud for
instance exploit the workflow
manager of the execution service to
do unattended cycles of operations
and control the system via VCR
3) Standalone Environment
IE is web service based,
any web service compliant
clients can reach it. This
mode of working is very
useful for small systems
and for prototyping and
debug large systems
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006
VCR
GPS
JSP
Algorithm and Key-Factor Example
• Remote method Y=F(X)
where Y,X are double
and F=
y= -1 if x<0
y=sqr(x) if x>0
The complexity (i.e. the algorithm that need to
be remotely executed) depend on the key
factor X
F. Lelli, Summer School on Grid Computing, Ischia, July 20, 2006