Tools for Composing and Deploying Grid Middleware Web Services

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Tools for Composing and Deploying Grid Middleware
Web Services
Dr. Aniruddha Gokhale Balachandran
Natarajan gokhale, bala_at_isis-server.isis.vanderb
ilt.edu ISIS, Vanderbilt University www.isis.vande
rbilt.edu/gokhale/PDF/DOA-GRID02.pdf
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Motivation

• Grid Applications require
• Multiple end-to-end QoS properties
• Secure, controlled access to resources from
  multiple service providers gt need individual
  SLAs
• E.g., collaborative scientific applications,
  virtual surgery

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Grid Application Development Challenges

• Tight coupling with COTS grid infrastructure
  middleware (GIMs)
• Proliferation of GIMs, such as Globus, ICENI,
  Legion
• Accidental complexities assembling and deploying
  grid applications

• Need to satisfy simultaneous multiple QoS
• Lack of resource reservation patterns
• No single sign-on secure access capability to
  resources
• Provisioning restrictions of COTS GIMs
• Difficulties in resource and QoS provisioning

Solution Use Model Integrated Computing tool
support to build Grid Applications and use Web
Services architecture to deploy them
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Model Integrated Computing (MIC)

• Modeling languages and environments themselves
  can be modeled as meta-models
• e.g., Generic Modeling Environment (GME)
  (www.isis.vanderbilt.edu)
• Analyze different but interdependent
  characteristics of GRID system behavior
• Synthesize platform-specific code customized
  for GRID applications

• Applies domain-specific modeling languages to
  engineer computing systems
• Provides rich modeling environment including
  model analysis and model-based program synthesis
• Modeling of integrated end-to-end view of
  applications with interdependencies
• Captures the essence of a class of applications

www.isis.vanderbilt.edu
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Model Integrated Computing (MIC)

• Advantages
• Free application developers from dependencies on
  any particular API
• Analyze models and provide correctness proofs
• Highly dependable and robust synthesized code
• Rapid prototyping of new concepts via modeling
  and interpretation
• Reducing time-to-market, saving costs, and
  preserving investments
• Resolve interoperability issues by synthesizing
  standard or custom code

www.isis.vanderbilt.edu
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Model Driven Architecture (MDA)

• OMG standardization of MIC paradigm
• Defines platform- independent models (PIMs) and
  platform-specific Models (PSMs)
• Uses Unified Modeling Language (UML) for modeling
• Real-time profile
• Dynamic scheduling profile
• Meta Object Facility (MoF) serves as meta-model
  repository
• XML Metadata Interchange (XMI) for meta-model
  exchange

www.omg.org/mda
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Component Synthesis with MIC (CoSMIC)

• Synthesizes code configuration metadata for the
  CIAO (CORBA Component middleware)
• Reusing components via compositions vs.
  generating new component implementations
• Composition of applications components CIAO
  plug-ins
• CIAO helps instantiating application processes
• MDA tool suite
• UML modeling using GME
• Analysis synthesis tools
• Enhancement to GME tool
• Uses MDA standards-based approach

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Grid TAO (GriT) Architecture

• Based on principles from DP-CORBA, RT-CORBA, CCM
• Seamless integration with GIMs via extensible
  transport capabilities
• Uses web-based interfaces for service
  provisioning
• Implemented using TAO and CIAO technology

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Grid Service Provider (GSP)

• Web service access to underlying middleware
• Single sign-on capabilities
• GSP maintains individual SLAs on behalf of user
• Collaborations via session initiation protocol
  (SIP)

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Meta-Resource Broker (MRB)

• Broker for resources
• Maintains abstractions of concrete resources
• Uses DP-CORBA parallel and part objects

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MRB Part Object Core

• Uses TAOs pluggable protocol framework to talk
  Grid protocols
• Used for resource discovery and reservation

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Integrating CoSMIC with GriT

• Proliferation of middleware
• UML modeling tools used to model DRE application
  behavior
• Model-first/generate-next strategy for finer
  grained control in components
• Simultaneous support for multiple QoS dimensions
• Model overall application QoS partitioning
• Compose application servers
• Model synthesize components
• Validate deploy
• Accidental Complexities
• Synthesize container QoS configurations metadata

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Model Driven Grid Middleware Deployment

• Context Grid applications are built using
  conventional infrastructure middleware

• Problem Hard to develop next generation grid
  applications because
• tight coupling with grid infrastructure
• accidental complexities
• satisfying multiple QoS requirements

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Model Driven Grid Middleware Deployment
Solution MDA-based tool, CosMIC, to compose and
deploy patterns from building blocks of GriT
middleware.
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Service Provisioning via CoSMIC GriT
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Model Driven Grid Web Service Deployment
Context Wireless and wired client need to
participate in collaborative grid applications
Problem Programming at the grid infrastructure
is too low-level. Standard based protocols and
interfaces must be used.

• Solution Services offered by GSP will be hosted
  as a web service.
• Similar to OGSA
• CosMIC can generate WSDL and help deploy these
  services

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MIC-DRE Middleware Integration

• Configuring and deploying application services
  end-to-end
• partitioning and distributing
• provisioning resources for QoS
• Composing components into application servers
• assemble semantically compatible QoS-enabled
  components from reuse repositories
• determining interconnections between components
  in metadata
• packaging components and metadata
• Configuring application component containers
• configuring right QoS policies for component
  containers
• maintain inter-component semantic compatibility
  w.r.t container policies

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MIC-Middleware Integration

• Synthesizing application component
  implementations
• synthesis of DRE components tailored to
  application e.g., for bounded worst case
  execution time under overload conditions
• bridge the gap between specifications and
  implementation via aspect weavers and generators
• Synthesizing dynamic QoS provisioning and
  adaptation logic
• synthesize adaptation logic using QoSket QDL
• Synthesizing middleware-specific configurations
• configuring threading models, buffering and flow
  control, levels of fault tolerance, transport
  protocols, demultiplexing strategies, security
• Synthesizing middleware implementations
• a more aggressive approach to synthesizing custom
  middleware

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Challenge 1 Configuration Metadata

• TAO/CIAO Configuration Modeling Language
• Interpreters synthesize XML or svc.conf files
• Will require modeling TAO/CIAO internals for
  configuration feasibility checking
• Can be applied to CORBA/CCM in general

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Challenge 2 RT-CCM Container Policy Modeling

• Container Policy Modeling Language
• QoS crosscutting concerns in container/component
  policies abstracted out
• Modeling of these cross cutting concerns
• Model interpreters synthesize container policies.

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Challenge 3 Component Synthesis Assembly

• Component Modeling Language
• Component logic modeling language
• Component interaction modeling language
• Synthesize CIDL
• Extend the Embedded Systems Modeling Language
  (ESML) designed for MoBIES

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Challenge 4 End-to-End QoS Assurance

• Two approaches
• Via aggregating required/offered QoS per layer
• Via required/offered QoS only at end points
• Modeling will depend on the approach chosen

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Summary of Ongoing Work

• RT/CCM (CIAO) being implemented at Washington
  University Vanderbilt University
• DP-CORBA being implemented jointly between
  Vanderbilt University UC Irvine
• CoSMIC tool suite, MRB being developed at
  Vanderbilt University
• All results will be available as open-source
  software

deuce.doc.wustl.edu/CIAO
www.isis.vanderbilt.edu/CoSMIC
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Concluding Remarks

• GriT enhances TAO/CIAO
• Meta resource broker
• Patterns for resource reservation and QoS
  adaptation
• Uses Model Integrated Computing tools
• MIC and GME details available at
• www.isis.vanderbilt.edu