Middleware solutions for integrated simulation environments

Jalali, Leila; Mehrotra, Sharad; Venkatasubramanian, Nalini

doi:10.1145/1891748.1891749

Cited by 1 publication

(2 citation statements)

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“…The meta-level is built on base-level simulators; structural reification 40 of base-level entities yields data structures at the meta-level which capture relevant aspects of each simulator in a meta-model and provides support for data adaptations and exchange across simulators. 41,42 Simulators interface with the meta-level by using wrappers. In our architecture, simulators’ data items are stored at base level simulators.…”

Section: A Reflective Architecture For Multisimulationmentioning

confidence: 99%

“…The first two steps are pre-processing steps that are human-in-loop process in which we would ask a user (for example, a data designer or administrator familiar with the simulators) to draw lines between elements that should contain related data in different simulators. Our methodology is described by Jalali et al 42,52 The minimum requirement for the simulator is the ability to stop and to proceed the simulation. When multisimulation runs, meta-level modules ensure the correctness until the end of simulation.…”

Section: A Reflective Architecture For Multisimulationmentioning

confidence: 99%

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Simulation integration: using multidatabase systems concepts

2014

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This paper considers the challenge of designing a framework that supports the integration of multiple existing simulation models into an integrated simulation environment (multisimulation). We aim to facilitate the process of fusing together the independently created simulators into an integrated simulation environment wherein we can model and execute complex scenarios involving multiple simulators. In this paper, we focus on solutions for the synchronization problem in multisimulation to orchestrate consistent information flow through multiple simulators. In particular, we provide: (1) a transaction-based approach to modeling the synchronization problem in multisimulations by mapping it to a problem similar to multidatabase concurrency; we express multisimulation synchronization as a scheduling problem where the goal is to generate “correct schedules” for time advancement and data exchange across simulators that meets the dependencies without loss of concurrency; (2) a hybrid scheduling strategy which adapts itself to the “right” level of pessimism/optimism based on the state of the execution and underlying dependencies. We also develop two key optimizations: (a) efficient checkpointing/rollback techniques; and (b) relaxation model for dependencies which guarantees bounded violation of consistency to support higher levels of concurrency. We evaluate our proposed techniques via a detailed case study from the emergency response domain by integrating three disparate simulators: a fire simulator (CFAST), an evacuation simulator (Drillsim) and a communication simulator (LTEsim).

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Section: A Reflective Architecture For Multisimulationmentioning

confidence: 99%

Section: A Reflective Architecture For Multisimulationmentioning

confidence: 99%