“…This is due to the likelihood that in some cases the messages do not arrive in time to be processed in one cycle of tick() calls. This behavior was also noted in [3] and is common for time-stepped execution models.…”
Section: Asynchronous Communicationsupporting
confidence: 60%
“…The first main issue is the completion of an LBTS computation by a specified deadline. Our real-time timemanagement implementation builds upon previous work in achieving repeatable real-time distributed simulations [3]. A primary challenge in repeatable performance is the timeliness is the tick() function.…”
SUMMARYDistributed simulation applications often rely on middleware to provide services to support their execution over distributed computing environments. Such middleware spans many levels, ranging from lowlevel support for data transmission through object request brokers to higher level, simulation specific functionality such as time management. We discuss design alternatives for realizing such middleware for hard real-time distributed simulations such as hardware-in-the-loop applications. We present the results from tests of a prototype implementation of real-time Run-Time Infrastructure middleware. Its performance is compared with a non-real-time implementation.
“…This is due to the likelihood that in some cases the messages do not arrive in time to be processed in one cycle of tick() calls. This behavior was also noted in [3] and is common for time-stepped execution models.…”
Section: Asynchronous Communicationsupporting
confidence: 60%
“…The first main issue is the completion of an LBTS computation by a specified deadline. Our real-time timemanagement implementation builds upon previous work in achieving repeatable real-time distributed simulations [3]. A primary challenge in repeatable performance is the timeliness is the tick() function.…”
SUMMARYDistributed simulation applications often rely on middleware to provide services to support their execution over distributed computing environments. Such middleware spans many levels, ranging from lowlevel support for data transmission through object request brokers to higher level, simulation specific functionality such as time management. We discuss design alternatives for realizing such middleware for hard real-time distributed simulations such as hardware-in-the-loop applications. We present the results from tests of a prototype implementation of real-time Run-Time Infrastructure middleware. Its performance is compared with a non-real-time implementation.
“…In the introduction we mentioned several works on protocols to solve the non-determinism issues of parallel execution (Fujimoto 2000) or real-time interactions (McLean and Fujimoto 2000). If we except these determinismrelated issues, repeatability is mainly a question of ensuring the long-term execution of a program.…”
Section: Solutions For Repeatability (Levels L1 and L2)mentioning
“…(Bacon and Goldstein 1991) classified non-determinism arising from input-data, system calls, and interrupts. Non-determinism arising from input data can be distinguished whether the input has been sent by logical processes, by externally running software, or by other sources, like human operators (McLean and Fujimoto 2000). Whereas in the context of Mole and for testing different planning agents (Uhrmacher and Gugler 2000) parallel, distributed simulators have been employed, for testing Autominder in the current virtual environment a sequential simulation suffices.…”
Section: Himmelspach Rohl and Lihrmachermentioning
confidence: 99%
“…Currently we are designing a paced distributed simulation system which uses time-stamped messages. The underlying concept is similar to (McLean and Fujimoto 2000) in utilizing time stamps for reducing non-determinism.…”
Section: While Simulation Not Yet Finishedmentioning
Agents are software systems aimed at working in dynamic environments. Simulation systems can be used to provide virtual environments for testing agents. The software to be tested, the objective of the simulation study, and the stage of the agent software development influences both: the environmental models used for testing and the mechanisms that synchronize the execution of agents and simulation. A clear distinction between model and simulation layer, and a modular design of the simulation system support the required flexibility. Based on the simulation system James (a Java based Agent Modeling Environment for Simulation) and two agent applications we will explore, how interfaces between virtual environments and software agents can be explicitly specified at the modeling level and suitable mechanisms for synchronization might be chosen on demand.
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