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
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