1 KidneyGrid: A Grid Platform for Integration of Distributed Kidney Models and Resources Xingchen Chu, Andrew Lonie , Peter Harris, Randy Thomas, Rajkumar Buyya Grid Computing and Distributed Systems (GRIDS) Laboratory Dept. of Computer Science and Software Engineering The University of Melbourne, Australia ww.gridbus.org Gridbus Sponsors 2 Outline Introduction What is KidneyGrid Design and Implementation Evaluation Live Demo Conclusion and Future work
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KidneyGrid: A Grid Platform for Integration of Distributed Kidney Models and Resources
Xingchen Chu, Andrew Lonie , Peter Harris, Randy Thomas, Rajkumar Buyya
Grid Computing and Distributed Systems (GRIDS) LaboratoryDept. of Computer Science and Software EngineeringThe University of Melbourne, Australiaww.gridbus.org
Gridbus Sponsors
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Outline
IntroductionWhat is KidneyGridDesign and ImplementationEvaluationLive DemoConclusion and Future work
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Introduction
Mathematical modeling has been used successfully in analyzing the huge volume of biomedical data
Such as modeling heart physiology, lung physiology, kidney physiology
Many models existVarious formatsVarious simulation environments
Generally proprietary and incompatibleExtremely difficult to access and integrate various models and resources
Various legacy kidney models and resourcesDifferent implementation techniques such as command line, graphical interface
4
Grid computing in e-Research
Grid computing providesPowerful computation facilities (means researchers can run their existing research faster)Other facilities such as working in collaborative environments, reducing costs, and gaining access to an increased number of resources and instruments
5
A typical e-Research vision
Researcher
Kidney Modeling molecular dockingBrain Analysis
Visualization
e-Research PlatformUser Manager
Resource Manager
Data Manager
Grid Scheduler
Computer Servers
Virtual Organization
Grid Host Environment
Globus Condor Alchemi
UNICORE XGrid PBS
ResearcherResearcher
Kidney Modeling molecular dockingBrain Analysis
Visualization
e-Research PlatformUser Manager
Resource Manager
Data Manager
Grid Scheduler
Computer Servers
Virtual Organization
Grid Host Environment
Globus Condor Alchemi
UNICORE XGrid PBS
Kidney Modeling molecular dockingBrain Analysis
Visualization
Kidney ModelingKidney Modeling molecular dockingmolecular dockingBrain AnalysisBrain Analysis
Visualization
e-Research PlatformUser Manager
Resource Manager
Data Manager
Grid Scheduler
Computer Servers
Computer Servers
Virtual Organization
Grid Host Environment
Globus Condor Alchemi
UNICORE XGrid PBS
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What is KidneyGrid?
An ARC e-Research Project developing a Grid platform for access to distributed kidney models and resources including
an interactive web interface to a collection of distributed legacy modelsa way to plan, execute and monitor the experiment over grid resourcesand a kidney virtualization to better present the outcome of the experiment
Part of the larger Physiome ProjectAn internationally collaborative open source project to provide a public domain framework for computational physiology
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System Architecture
eResearchGrid Portal
GridBroker
KidneyModel1
KidneyModel2
KidneyModel3
(Medullary urine-concentration model)
(TGF Simulation)
(Proximal Tubule Simulation)
QuantitativeKidney database
at Melbourne
Australian Server
Kidney Model
Registry
Duke University, USA
Evry, France Server
Cornell University,USA
VO andAuthorization
Service
ExperimentPlan
Result Archivalwith meta data
Melbourne Server
ResultsVisualisationon Desktop
AdvancedVisualisation
Facility
VPAC, Melbourne
1
2
3
4
5
6
6
6
7
8
9Melbourne Grid
Server
eResearchGrid Portal
GridBroker
KidneyModel1
KidneyModel2
KidneyModel3
(Medullary urine-concentration model)
(TGF Simulation)
(Proximal Tubule Simulation)
QuantitativeKidney database
at Melbourne
Australian Server
Kidney Model
Registry
Duke University, USA
Evry, France Server
Cornell University,USA
VO andAuthorization
Service
ExperimentPlan
Result Archivalwith meta data
Melbourne Server
ResultsVisualisationon Desktop
AdvancedVisualisation
Facility
VPAC, Melbourne
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22
33
44
55
66
66
66
77
88
99Melbourne Grid
Server
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Issues to be addressed
Standarda platform for ‘plug and play’ modelinga standard basis of representation for all models and their data
InteroperabilitySufficient legacy kidney models for the site to be opened to the general community Integration of various legacy application written by different programming language
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Technology choices
Presentation Layer
User Level Middleware Layer
Grid Middleware Layer
Gridsphere Framework
Java Server Faces
Java Applet
Gridbus Broker
Web Service Resource Framework (WSRF)
Globus & Alchemi
Work Station, Server or Cluster
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Web Portal Development
User interface for the researchersUtilize Gridsphere Framework
open source and JSR 168 (Java portlet standard) compliantReusable modules such as user managementmature and widely used by other grid portal related projects
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Legacy Application Integration Model (Explicit Model)
Explicit Model (typical of GT-2) (J. Giddy et. al, 2005)
Client
Application &Data files
Site A
User A
User A
Site B
Processing Service
Imported Application
1
2 3
User explicitly specifies the resources, executable program, program’s arguments and environment, and data files. User takes full responsibility to update it
User A
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Legacy Application Integration Model (Wrapper Model)
Wrapper Model (Web Services based) (J. Giddy et. al , 2005)
Client
Data files
Site A
User A
User A
Site B
Application Wrapper Service
Local Application
1
2 3
Service Provider
Application is hide to user to avoid dependencies between client and service providerUser don’t need an account on the site running the applicationAuthorization to use the service can be controlled by the service provider
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Legacy Application Integration
Avoid dependencies on the legacy applicationNeed a generic way to communicate with various models
Adopt the wrapper model for integrationImplement a service wrapper for each models
Utilize the Web Service Resource Framework (WSRF)It is stateful (useful for long running simulation)Can be deployed into globus container (make each model a grid service)Support Windows Platform via WSRF.net and Alchemi
For each service wrapper, we implementA WS-Resource for each model representing possible state such as parameters or simulation statusA WS-Notification mechanism for long running simulation
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Grid Resource Broker
Gridbus Broker is a user-level middlewareEasy to use
Pure Java-Based, Open Source, Well-Documented Services including application composition, scheduling, monitoring, result collection and QoS
Flexible and ExtensibleHigher level abstraction for various low level grid middleware such as globus, unicore, achemi etc.
ScalableLeast State: stateful information are stored in DB other than memoryWSRF interface for the Broker: can be deployed as web services
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Experiment Plan and Execution
Prepare the experiment by modifying the parameters via web pagesSubmit the experiment plan to the Gridbus BrokerExecute simulation on remote grid resources via the service wrapperMonitor the execution of the experiment
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Visualization
Need to generic visualization facility to demonstrate all the modelsRequire a standard format to represent the underlining data (XML schema)Transformation from various results into the standard data format
Utilize XSLT transformation (provide a stylesheet for each kidney model), not be able to handle non-xml format dataOther transformation technique for non-xml format data
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Evaluation
XML Results
User Request
Web Interface
Create Jobs
Gridbus Broker
GT-4 Resource
KSim Factory Service
Dispatch simulation job and collect result
KSimService (multiple KSim Resources)Transformation
Engine
Target XML
An integrated kidney model called KSim (written by fortune language)
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Portal Snapshot (I)
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Portal Snapshot (II)
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Portal Snapshot (III)
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Portal Snapshot (IV)
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Experiment (I)
The possible simulation cases for KSim
T is the total number of cases, s (5), t (7), r (4), x (3) stand for solute, tube, region and extra parameter respectively, fn (3) and fx(31) are the acceptable factor for basic and extra simulation The total number is then 513
111111xn fxfrts CCCCCCT ×+×××=
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Experiment (II)
We tested 53 cases on 3 grid resources
44%
30%
26%
manjra.cs.mu.oz.auhorowitz.cs.mu.oz.au
ngtest.vpac.org
0
10
20
30
40
50
60
Simulation Cases
Time (second)
Sim 1
Sim 2
Sim 3
Sim 4
Sim 5
Sim 6
Standalone
15212915
0 500 1000 1500 2000 2500 3000 3500
Simulation
Approach
Time (second)
Standalone
KidneyGrid
(a) Job Completion Rate (b) Average Job Execution Time
(c) Total Job Execution Time
44%
30%
26%
manjra.cs.mu.oz.auhorowitz.cs.mu.oz.au
ngtest.vpac.org
0
10
20
30
40
50
60
Simulation Cases
Time (second)
Sim 1
Sim 2
Sim 3
Sim 4
Sim 5
Sim 6
Standalone
15212915
0 500 1000 1500 2000 2500 3000 3500
Simulation
Approach
Time (second)
Standalone
KidneyGrid
(a) Job Completion Rate (b) Average Job Execution Time
(c) Total Job Execution Time
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Advantages of the KidneyGrid
ScalableSeparate the portal process and Gridbus broker process into different JVM increase both the scalability and performance of the system we achieve this utilizing the new WSRF interface for Gridbus Broker
SecureThe wrapper model for integrating legacy application enhance thesecurityThe service provider controls the service they want to provide to the usersUsers won’t need to upload the executable program to the grid resource which may generate security concerns
ExtensibleEasy to extend to support other kidney models once required
HeterogeneousSupport diversity of kidney models and resources
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Live Demo
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Conclusion and Future Work
A grid platform for distributed kidney models has been developed
Experiment plan, execution, monitoring and visualizationIntegration of the legacy application (KSim) into system based on web services
Integration of more legacy kidney modelsTransformation for each model to a generic visualization toolImplementing VO-based scheduling, resource discovery and management.
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Thanks for your attention!
We Welcome Cooperation in Research and Commercialisation!http:/www.gridbus.org | http://www.gridbus.com
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Reference
B. Beeson, S. Melnikoff, S. Venugopal, D. G. Barnes. A Portal for Grid-enabled Physics, Technical Report, GRIDS-TR-2004-9, GRIDS Laboratory, University of Melbourne, Australia, Oct 19, 2004.H. Gibbins, K. Nadiminti, B. Beeson, R. Chhabra, B. Smith, and R. Buyya. The Australian BioGrid Portal: Empowering the Molecular Docking Research Community, Proceedings of APAC 2005, Sept. 26-30, 2005, Gold Coast, Australia Z. Zhou, F. Wang and B.D. Todd. Development of Chemistry Portal for Grid-enabled Molecular Science. Proceedings of the e-Science 2005, Dec. 5-8, 2005, Melbourne, Australia.L. Zhou, A. Matsunaga, V. Sanjeepan, H. Lam and J. A. B. Fortes, Application Modelling and Representation for AutomaticeGrid-Enabling of Legacy Applications, Proceedings of the e-Science 2005, Dec. 5-8, 2005, Melbourne, Australia.
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Technology choices
Provide supports for integration of grid resources accessible through low level grid
middlewares
Globus Toolkit 4, Alchemi, UNICORE
Core Grid Middleware
Provide Java Applet that can be easily integrated into web portals
VPAC Advanced Visualization Facility in
Melbourne
Visualization
WSRF provides stateful web service which is able to deployed on the globus toolkit 4 (gt-4)
container
Web Service Resource Framework (WSRF)
Service Wrapper for Legacy
Kidney Model
Provide ability to support Web Service Resource Framework (WSRF), various scheduling
algorithms and resources such as globus and alchemi
Gridbus Broker V3.0Grid Resource Broker
Only consider the authentication for the VO, may extend to completed VO system such as
VOMS
MyProxyVirtual Organization
Reusable web components. JSR 168 portletstandard compliant. Open source and widely
used for grid portal development.
Gridsphere FrameworkPortal
CommentsTechnology UsedComponent
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