SIMULATIONS

 

            PSI defines a simulation as one or more tasks running on a computer, typically taking in files, interactive inputs, and real-time channel feeds.  Simulations produce graphical or literal data outputs to interactive screens, files or real-time channels.  Using GSS, simulations can be run multiple times automatically for parametric or sensitivity analysis, or under the GSS optimization facility.  Models are built to represent entities that are incorporated into a simulation.  Models must contain sufficient detail so that, when a simulation is run, the measures of performance or effectiveness produced are sufficiently accurate to meet validity requirements on the results.

 

            Listed below is a sampling of simulations that PSI has provided to clients over the past fifteen years.  Since most of PSI's clients are engaged in communications technology, this list is somewhat limited to communications simulations.  Prior to this listing is a description of  network connectivity simulations and capacity simulations.  Simulations built over the past five years contain combined connectivity and capacity models working together.  As simulations get large, or when simulations are required to play with other simulations, then users can use the GSS distributed simulation environment to run multiple simulations over a network of distributed platforms.

 

NETWORK CONNECTIVITY SIMULATIONS

 

            Network connectivity can be determined for wired and wireless transmission systems based on models for backbone and access nodes as well as individual mobile subscribers.  This covers multichannel links including antennas, interference, mobile telephones and their dynamic movement on rough terrain and in foliage.  These simulations can be used to assess the connectivity of a complete network.  This provides for simulation of a large nodal system with highly directional antennas and multiple dynamic interference sources to allow detailed analysis of network connectivity, vulnerability, and susceptibility.  Nodes can be on helicopters, fast moving aircraft, and satellites with orbital equations describing the motion and position at intervals specified by the user so that changing connectivity can be used to assess adaptive network management algorithms dynamically.

 

 

NETWORK CAPACITY SIMULATIONS

 

            Network capacity can be determined at all levels of resolution by simulations based on GSS models for backbone and access nodes, aggregated subscriber facilities, detailed voice subscribers, and client-host data system traffic.  These simulations are designed to incorporate specific instrumentation models to analyze the capacity of an active network under realistic stress conditions including dynamic link error rates generated from the connectivity models, and equipment downtime.  Detailed models of all protocol layers and routing algorithms are also incorporated in these models.  These include adaptive algorithms for flooding, contention access, TDMA, CDMA, FDMA, as well as other standard routing methods.

 

 

COMBINED SIMULATIONS

 

            As requirements for simulations grow, and multiple equipments and systems must be represented to provide more realistic overall assessments of complex scenarios, it becomes necessary to bring models of many systems together into a single simulation.  These systems can represent intelligence systems, EW systems, weapon systems, logistic systems, and command and control systems, as well as the combination of connectivity and capacity.  GSS has prevailed as the ideal framework for these large scale simulations, with models at varying resolutions and large numbers of moving platforms to insure validity of results.

 

 

DISTRIBUTED SIMULATIONS

 

            As the need for combined simulations grow, the interaction of multiple simulations running together becomes a desired solution approach.  This allows the area experts to focus on the problem they are trained to solve, as long as the inputs from sources that feed their environment are included.  Most often, the interaction between these different systems affects the outcome of one or both, and must be accounted for as the scenario unfolds.  Data coherency and time synchronization become the problems to solve, and these are automatically solved with GSS.

 

 

            Next                 Previous                       Home