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2015-07-23 09:00:00
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MS4 Me version 3.0 Released

MS4 Systems, subsidiary of RTSync Corp. releases the new MS4 Me version 3.0 with revolutionary features including Markov Modeling capability. MS4 Me is a powerful DEVS-based environment for design, development, and implementation of IT-integrated systems of systems. Markov Modeling is among the most commonly used forms of model expression. For example, the Wikipedia entry for Markov Chains lists examples from the following disciplines.
  • Physics
  • Chemistry
  • Speech Recognition
  • Information sciences
  • Queueing theory
  • Internet applications
  • Statistics
  • Economics and finance
  • Social sciences
  • Mathematical biology
  • Genetics

These and many other applications are evident from googling the Internet. 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.
For more information on Markov Modeling and other new capabilities of MS4 Me, please visit and download the Trial version and follow the User Guide and examples. MS4 Me enables design and evaluation of flexible architectures for multiple data products targeted to multiple consumers with a support of flexible software and hardware implementation of high level design. It promotes collaboration among developers and users by sharing and distributing models through Cloud-based Modeling and Simulation infrastructure. MS4 Me is the first commercial DEVS toolset designed by Dr. Bernard Zeigler. It is implemented with Eclipse RCP technology providing easy-to-use sequence diagram, natural language interface, and System Entity Structure ontology features. For more information, you can contact us at