MS4 Me
MS4 Me allows you to design, engineer, visualize and test in a single,
environment without compromising rigor, quality or performance
MS4 Me was designed to provide
Better communication between Stakeholders, Managers, Engineers and
Technicians through an easy to use natural language interface;
Interoperability from the beginning through built-in syntactic and
semantic checking of data and models;
Immediate Simulation and Visualization of the models YOU make;
Ease of use and powerful extensibility from simple processes to
complex mathematical functions;
Managers - lay out the architecture of the system, process, or
solution you envision then hit the animate button and watch the
information and process flow. If it is not to your liking, MS4
Me makes it iterate as needed. Run animations to demonstrate and
explain your design to stakeholders;
Software developers - start from the manager's model as a set of
requirements. Using your model repository when suitable, refine
the model by replacing MS4 Me's animation-generated stubs with
realistic components. If needed easily amend the manager's information
and process flows;
Information engineers - couple this model with those of other systems
with which it must interoperate. Use MS4 Me's integrated data engineering
utilities to harmonize API's and simulate to watch that the information
flow is as specified. Include security considerations as required;
Technicians - export the model to your choice of a DEVS simulator to meet
execution requirements. The model will run correctly whatever the platform,
whether single processor, distributed, or web.
Translating Needs into Requirements and Requirements to Implementations has
always been a challenge, but the complexity of today's Systems of Systems makes
it even more difficult to communicate clearly across diverse subject domains and
experts. MS4 Me promotes better communication through a restricted natural language
interface; internal syntactic and semantic checking; immediate visualization.
Engineering data to carry the intended meaning, syntactically, semantically and
pragmatically has always been a challenge, making your data interoperable with other
systems' data is even more challenging. MS4 Me improves
your ability to create data
schema that are engineered for interoperability and completeness of meaning in context
of the systems that produce and consume your data. MS4 Me's integrated modeling and data
engineering facilities allow
you to watch simulated data exchanges and ensure that your
models consume and produce the data you specify at the right time and place.
MS4 Me supports easy sharing of modeling projects encouraging team-based development.
Projects developed in one computer can easily be transferred to another and immediately
executed. For more advanced collaborative development, we offer web-based model development
and execution.
Traditional computer based M&S has enabled managers and engineers to evaluate complex scenarios
and design alternatives for many years. However, traditional, discipline-based M&S solutions face
great challenges to analyze today's highly multi-disciplinary problems.
DEVS (Discrete Event System Specification) enables the advanced modeling & simulation and provides novel
system analysis & design methodology. MS4 Me is a tool set for discrete event modeling and simulation of
complex systems. The DEVS (Discrete-Event System Specification) formalism provides an engine for advanced
M&S technology to support "virtual build and test." This formalism has been applied to solving complex
problems for over three decades. MS4 Me provides a powerful environment that incorporates the information
of system structure as well as component behavior in an integration platform. The result is a high flexibility
platform to realize hierarchical M&S with various abstraction levels. Capability to implement different system
abstractions, and to control problem complexity, gives MS4 Me the power to execute analyses ranging from simple
to highly sophisticated.
MS4 Me provides various features that enable modeling and simulation of complex system in efficient manner
Hierarchical models are coupled models with components that may be atomic or coupled models that
constitute
a part of the entire system. Hierarchical construction is a stage-wise process that enables testing
and
verification at each stage before proceeding to the next stage.
The class hierarchy of MS4 Me allows you to readily start writing full-fledged models in its underlying
formalism.
Parallel DEVS differs from Classical DEVS in allowing all imminent components to be activated
and to send their
output to other components concurrently, thereby capturing real world parallelism.
The DEVS SimViewer is a utility included in the MS4 Me framework to view and check that all the models
and
couplings are present and working as expected. In addition, SimViewer allows you to run, observe
and evaluate
the real-time execution of the system under development. You can step one transition at
a time, run, pause, and
restart the execution of the model and watch the messages received and state
transitions made, by each of the
components at a speed you choose. This helps you detect flaws quickly
and easily.In addition, MS4 Me SimViewer
allows the developer to step through and drill into each state
transition of a hierarchical model to any depth. This
allows you to narrow and widen the scope of
visualization and testing to find problems at early stages of the
development.
Operating System Window OS Series, Linux and Unix series
Java™ J2EE JVM 2.0 or higher
Minimum Requirement RAM 2GB, HDD 10GB
Markov Modeling is among the most commonly used forms of model expression.
For background in Markov chains and other forms of Markov state-based modeling consult the
above link and other articles in Wikipedia. Besides their general usefulness, the Markov
concepts of stochastic modeling are implicitly at the heart of most forms of discrete
event simulation. Indeed, such concepts are fully compatible with the Discrete Event
Systems Specification (DEVS) characterization of discrete event models and a natural
basis for the extended and integrated Markov modeling facility developed within the
MS4 Me M&S environment. The facility described in this Guide offers an easy-to-use
set of tools to develop Markov models which are full-fledged DEVS models and able
to be integrated with other DEVS models just like other DEVS models. From this point
of view, the facility makes it much easier to develop probabilistic/stochastic DEVS
models than was previously. It does this by automating a lot of the development tasks
that you would otherwise have to do manually. Therefore this facility raises the power
of model development afforded by MS4 Me to a new level of speed and quality assurance
that is unparalleled in all other commercial and academic tools on the market. Using it
you will be able to develop families of DEVS models for cutting edge challenging areas
such as Systems of Systems, agent-directed systems, and DEVS-based development of
Web/Internet of Things. Finite state Markov chain model classes (Kemeny and Snell, 1960, Feller, 1966),
with both discrete and continuous time bases, have been implemented in MS4 Me using the FP-DEVS
capabilities. The three available modeling classes are: Continuous Time Markov Model (CTM),
Discrete Time Markov chain (DTM) and the Markov Matrix (MM) class. Continuous Time Markov Models can
represent complex systems at the level of individual actors. Each actor can be represented as a CTM
with states and transitions as well as inputs and outputs that enable them to interact as atomic
models within coupled models using coupling in the usual way. Briefly stated, these atomic and
coupled models are useful because:
The DEVS simulator provides a Monte Carlo layer that generates stochastic sample space behavior
You can use DEVS Markov models to express probabilistic agent-type alternative decisions and consequences
Together with experimental frames, DEVS Markov models support queuing-like performance metrics
(queue sizes, waiting times, throughput, losses)
You can generate and analyze both transient and steady state behavior
Markov Finite Chain Matrix (MM) Models are computationally much faster because they employ deterministic
computation of probabilities interpreted as frequencies of state occupation of the corresponding CTMs.
Such models are very useful because:
They yield probabilities for ergodic CTMs in steady state
They yield probabilities for CTMs that reach absorbing states
They support computation of state-to-state traversal times for models where time consumption is of
essential interest
They provide simplifications of CTMs that are accurate for answering certain questions and can be
composed to yield good approximations to compositions of CTMs.
MS4 Me features use of the System Entity Structure (SES) simulation modeling ontology in
easy-to-use-form for model development and experimentation management.
MS4 Me implements the two main pillars of DEVS and SES to make the new environment a powerful and
efficient platform to develop a virtual build and test of complex Systems of Systems.
MS4 Me includes or provides the following capabilites:
DEVS Integrated Development Environments;
Finite Deterministic DEVS;
System Entity Structure (SES);
Decomposition and Coupling;
Hierarchical Construction;
DEVS Natural Language Models and Elaborations;
Elaborating FDDEVS into Fully Capable Models in Java;
Specialization and Pruning;
Aspects and Multi-aspects;
Inheritance in Pruning;
Automated and Rule-Based Pruning;
DEVS Simulation Protocol;
Dynamic Structure: Agent Modeling.
Through the cloud based model store, it is easy for teachers and students to exchange DEVS models
within
a course setting and for developers to collaborate across the web. More information can be
found from the
new book, Guide to Modeling and Simulation of Systems of Systems