Interoperability, Automation, Builtin Evolution: the DEVS Framework for Coping with Emerging Complex

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Interoperability, Automation, Built-in Evolution
the DEVS Framework for Coping with Emerging
Complexity

• Bernard P. Zeigler
• Arizona Center for Integrative Modeling and
  Simulation
• University of Arizona, Tucson
• and
• RTSync Corporation

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IT Systems Developmental Complexity?

• IT Systems Developmental Complexity
• degrees of developmental freedom
• interdependence of design decisions
• special requirements of environments
• IT Complexity explosion
• is driven by faster, cheaper computers,
  networking, web middleware, ,
• Emergence each stage enables the next stage with
  accelerating options for further growth
• Wherever choices in platform, language,, line of
  code, are possible, different developers will
  make different choices
• Underlying structure/behavior dependencies force
  local decisions to have global impact breaking
  neat design patterns
• Environments impose a plethora of special
  situations and an exponentially growing number of
  parameter combinations.

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• Consequences of complexity explosion
• Proliferation of incompatible variations on same
  themes
• Ubiquitous heterogeneity
• Vertical integration - Stove piping

• Response Model-Driven Development Methodology
• is increasingly being adopted for
  software-intensive system development
• In this context, model is an abstract
  representation of software code, that
• is technology independent
• can survive technology changes
• can be implemented in multiple code
  instantiations
• enables reuse and automation

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UML (Unified Modeling Language)

• Is the most widely used framework to support
  model driven development
• Promoted by Object Management Group as a
  standard within its Model Driven Architecture
  (MDA)
• Supported by increasingly powerful commercial
  tools
• Enhanced by SysML supporting requirements front
  end
• Incorporated in architectural frameworks DoDAF,
  MoDAF,

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Issues In Developmental Complexity of IT Systems

• Often development does not start from scratch
• Conditioned by idiosyncratic requirements
• Powered, but unconstrained, by applicable
  standards
• Requires legacy subsystem integration
• Rigorous testing is needed to cope with
  complexity
• Methodology must scale with growth and evolution
  of system
• UML/MDA offers only limited support to address
  these concerns

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Formulate the Issues within a Formal System of
System Models (SoSM) Concept

• SoSM collection of disparate system models to
  be federated to satisfy new simulation
  requirements
• Each participating system model may itself be
  large and complex
• Participant models usually have become efficient
  at achieving their own specialized requirements
• Participant models often adhere to idiosyncratic
  formalisms and development approaches
• Distinguish between interoperation and
  integration to set appropriate objectives

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Interoperation vs Integration

• Interoperation of system components
• participants remain autonomous and independent
• loosely coupled
• interaction rules are soft coded
• local data vocabularies persist
• share information via mediation

• Integration of system components
• participants are assimilated into whole, losing
  autonomy and independence
• tightly coupled
• interaction rules are hard coded
• global data vocabulary adopted
• share information conforming to strict standards

reusability composability
efficiency
NOT Polar Opposites!
adapted from J.T. Pollock, R. Hodgson,
Adaptive Information, Wiley-Interscience, 2004
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DEVS Framework

• Discrete Event Systems Specification (DEVS) is
  the basis for a formal framework for modeling and
  simulation
• DEVS contributes to scalability by
• Offering a standard for distributed simulation to
  support interoperability, composability, and
  reuse
• Exploiting the separation between model,
  experimental frame and simulator
• Fostering model continuity and progressive
  development
• Automating and integrating complex systems
  implementation and testing
• Emulating the biological brain for its "built-in"
  correlation of activity and behavior to drive
  efficient evolution via component re-us

DEVS is not a technique, method or technology
But it can leverage technology to add implement
its contributions in
particular Web Service Technology
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Web Service Oriented Architecture Basis for MS

• Language and platform independent gt
• separation of specification and implementation
• Loosely coupled gt
• message based, synchronous and asynchronous
  interactions.
• Net-Centric gt
• No centralized control, use of established
  protocols, security considerations.
• Inter-operable gt
• Standards based
• Observable gt
• agents can inspect service
  requests/responses

Transport protocol HTTP/HTTPS
request/response Data Encoding SOAP (Simple
Object Access Protocol), XML Schema Interface
Description WSDL (Web Services Description
Language) Service Description and Discovery UDDI
(Universal Description, Discovery and
Integration) Security WS-Security,
XML-Signature, XML-Encryption, ...

• Emerging infrastructure gt
• Net-Centric Enterprise Services on the Global
  Information Grid
• Basis for Model Registration and Discovery gt
• Meta-Data Registry
• Basis for Simulation gt
• Web server and service development
  frameworks ( .Net, AXIS)
• Emerging advances gt
• Mediation services, Semantic Web

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Approach to Current Issues in SoSM

• Adopt Web-enabled MS Concepts for composing SoSM
• Exploit SOA infrastructure for Model Repository
  and Component Reuse
• Develop Formal Dynamic SoSM Distributed
  Simulation Standard
• Build on this foundation to support Higher Levels
  of Interoperability
• Develop automated and integrated development and
  testing methodology

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SOA-enabled Model Repository Composability and
Reuse
adapted from ZEIGLER, B. P. 1997. A framework
for modeling simulation. Applied Modeling
Simulation An Integrated Approach to Development
Operation, McGraw-Hill, New York.
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Success Story DEVS-based Joint MEASURE Model
Repository Reuse
the Lockheed-Martin activities may well
represent the state of the art in complex model
composability , Improving the Composability of
Department of Defense Models and Simulations,
P.Davis and R.Anderson RAND, 2004
Use of infrared model in JCTS project
Note presence of discrete and continuous dynamic
model types
Advanced Simulation Center, Lockheed Martin
Corp., Sunnyvale, CA
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Linguistic Levels of Information Exchange and
Interoperability
System Participant
System Participant
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DEVS Standardization Supports Higher Level
Web-Centric Interoperability
DEVS Simulation Concept
pragmatic
semantic
syntactic
DEVS Model Specification
DEVS Protocol
DEVS Simulation Protocol
Services
Schemata
Registry
XML
SOAP
Network Layers

• DEVS Protocol specifies the abstract simulation
  engine that correctly simulates DEVS atomic and
  coupled models
• Gives rise to a general protocol that has
  specific mechanisms for
• declaring who takes part in the simulation
• declaring how federates exchange information
• executing an iterative cycle that
• controls how time advances
• determines when federates exchange messages
• determines when federates do internal state
  updating

Note If the federates are DEVS compliant then
the simulation is provably correct in the sense
that the DEVS closure under coupling theorem
guarantees a well-defined resulting structure and
behavior.
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Web-enabled interoperability of DEVS components
Supports re-use, composability,
and interoperability

• DEVS Message Class is defined in the formalism
• Schemata for entity classes in Message are
  stored in namespace
• DEVS Federates can register and discover
  schemata for information exchange

DEVS Namespace
Can be automated for JAVA using Dynamic
Invocation
DEVSJAVA client
DEVS coordinator
Proxies
DEVS coupled Model
DEVS Messages
JRE
SOAP messages
IP Network
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Biologically Inspired Assessment for Component
Re-use
DEVS Agent
DEVS Agent
collector
Http Requests/ responses
IP Network
Mission Thread Evaluation
Component Credit Assignment
Information for Future Component Re-use
Activity Tracking
Correlations of activity with Mission Thread
Success
Component benefit and resource cost in context
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DEVS-Based Net-Centric Systems Test Agent
Capability
TE Instrumentation sites
users
Mission Thread
clients
Mission Effectiveness
Information Exchange
servers
System Performance
workstations
networks
Middleware
Network Monitoring
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Summary 

• Model-driven methodology employs
  technology-independent software abstractions,
  e.g., in UML, to support diverse implementation
  platforms and enable reuse and automation
• Existing interoperability standards do not
  provide needed separation between models and
  simulations and do not effectively constrain
  object models
• System of System Modeling (SoSM) concepts go
  beyond UML/MDA to address issues in
  interoperability, composability, and reuse
• DEVS system theory based framework
  operationalizes SoSM concepts and supports
  automated, rigorous testing in realistic GIG/SOA
  environments

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Books and Web Links
www.acims.arizona.edu
Rtsync.com
devsworld.org
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More Demos and Links http//www.acims.arizona.edu
/demos/demos.shtml

• Integrated Development and Testing Methodology
• AutoDEVS (ppt) DEMO
• Natural language-based Automated DEVS model
  generation
• BPMN/BPEL-based  Automated DEVS model generation
• Net-centric SOA Execution of DEVS models
• DEVS Unified Process for Integrated Development
  and Testing of SOA
• Intrusion Detection System on DEVS/SOA

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DEVS/SOA Infrastructure Supports Deployment and
Execution of DEVS Models on the Web

• Service Oriented Architecture (SOA) consists of
  various W3C standards
• Machine-to-machine interoperable interaction over
  the network based on WSDL interface descriptions
• Client server framework
• Message encapsulated in SOAP wrapper which is in
  XML

Run Example
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Example of GIG/SOA Mission Thread Testing

• Test agents are DEVS models and Experimental
  Frames
• They are deployed to observe selected participant
  via their service invocations

• MAJ Smith tasks Intel to reconnoiter objective
  area and provide threat estimate
• 2. Posts taskings using
  Discovery and Storage

3. Intel Cell initiates high priority
collection against objective, and
collectors post raw output 4. Intel posts
products via Discovery and Storage
5. Intel Cell issues alert via messaging

• MAJ Smith pulls
• estimate from Storage

NCES GIG/SOA