Download Interoperability, Automation, Built-in Evolution

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
1
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.
2
•
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
3
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, …
4
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
5
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
6
Interoperation vs Integration*
Interoperation of system components
Integration of system components
•
•
•
•
•
•
participants remain autonomous and
independent
loosely coupled
interaction rules are soft coded
local data vocabularies persist
share information via mediation
•
•
•
•
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
7
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
8
Web Service Oriented Architecture Basis for M&S
Services
Registries
Data
Data Type Schema and Instances
XML
SOAP
Network Layers
Transport protocol
Language and platform independent =>
separation of specification and implementation
Loosely coupled =>
message based, synchronous and asynchronous interactions.
Net-Centric =>
No centralized control, use of established protocols, security
considerations.
Inter-operable =>
Standards based
Observable =>
agents can inspect service requests/responses
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 =>
Net-Centric Enterprise Services on the Global
Information Grid
Basis for Model Registration and Discovery =>
Meta-Data Registry
Basis for Simulation =>
Web server and service development frameworks
( .Net, AXIS)
Emerging advances =>
Mediation services, Semantic Web
9
Approach to Current Issues in SoSM
• Adopt Web-enabled M&S 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
10
SOA-enabled Model Repository Composability and Reuse *
Requirement
In relation to
Supports
Components and
Coupling
Creating new compositions
composability
reusability
building block
components for
application areas
defining a small number of
“primitives” for synthesizing a
wide variety of models for
specific domain
expressability
reusability
hierarchical
modular model
construction
input/output ports for both
building block components and
coupled models
composability
complexity management
experimental
frame base
indexing
supports discovery of frames
instantiated in the model base
that are related to a desired
frame for given objectives
meta data characterization
discovery
accommodate
multiple
formalisms
enable using different types of
models with specific semantics,
advantages, and limitations
expressabilty
interoperability
* adapted from: ZEIGLER, B. P. 1997. A framework for modeling & simulation. Applied Modeling & Simulation:
An Integrated Approach to Development & Operation, McGraw-Hill, New York.
11
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
GPS III
Use of infrared
model in JCTS
project
Note presence of discrete and continuous dynamic model types
*Advanced Simulation Center, Lockheed Martin Corp., Sunnyvale, CA
12
Linguistic Levels of Information Exchange and Interoperability
Linguistic
Level
A System of Systems or services interoperates at this
level if :
Pragmatic – how information in
messages is used
The receiver re-acts to the message in a manner that the
sender intends (assuming non-hostility in the collaboration).
Semantic – shared understanding
of meaning of messages
The receiver assigns the same meaning as the sender did to
the message.
Syntactic –common rules
governing composition and
transmitting of messages
The consumer is able to receive and parse the sender’s
message
pragmatic
pragmatic
semantic
semantic
syntactic
syntactic
System Participant
System Participant
13
DEVS Standardization Supports Higher Level
Web-Centric Interoperability
DEVS Simulation Concept
pragmatic
semantic
syntactic
DEVS
Model
DEVS
Protocol
DEVS Model Specification
DEVS Simulation Protocol
Services
DEVS
Simulator
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.
14
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
DEVSJAVA client
DEVS
Namespace
aDEVS Federate
DEVS
coordinator
JRE
DEVSJAVA Federate
DEVS Simulator
Services
In C++
Proxies
DEVS coupled
Model
Can be automated
for JAVA using
Dynamic Invocation
.Net
DEVS
Model
DEVS Simulator
Services
In JAVA
DEVS
Messages
Microsoft web server
SOAP
messages
IP Network
AXIS2
DEVS
Model
Apache tomcat server
Biologically Inspired Assessment for Component Re-use
DEVS Federate
DEVS Coordinator
Non-DEVS Federate
DEVS coupled
Model
Simulator
Services
DEVS
Model
Web server
web server
DEVS
Agent
JRE
collector
Http
Requests/
responses
DEVS
Agent
DEVS
coordinator
DEVS Simulator
Services
IP Network
Mission Thread
Evaluation
Activity
Tracking
Component
Credit
Assignment
Correlations of
activity with Mission
Thread Success
Information for Future
Component Re-use
Component benefit and
resource cost in context
DEVS-Based Net-Centric Systems Test Agent Capability
users
T&E
Instrumentation
sites
Mission Thread
System Performance
Middleware
servers
workstations
networks
Information Exchange
clients
Mission Effectiveness
Pragmatic
Agents
Semantic
Agents
Syntactic
Agents
Network Monitoring
17
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
18
Books and Web Links
devsworld.org
www.acims.arizona.edu
Rtsync.com
19
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
20
DEVS/SOA Infrastructure: Supports Deployment and Execution of DEVS
Models on the Web
WEB
SERVICE
CLIENT
DEVS
Agent
(Observer)
DEVS
Agent
( Virtual User)
DEVSJAVA
DEVS Modeling Language (DEVML)
WEB
SERVICE
CLIENT
DEVS Simulator Services
Middleware (SOAP, RMI etc)
Net-centric infrastructure
•
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
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
Observing Agent
for Major Smith
Observing Agent
for Intel Cell
1. MAJ Smith tasks Intel to
reconnoiter objective area and
provide threat estimate
Observing Agent
alerts other Agent
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
notes time of posting
5. Intel Cell issues alert via messaging
6. MAJ Smith pulls
estimate from Storage
sends time to other Agent
Computes Time for Task,
Measure Performance
NCES GIG/SOA
22