Deriving feasible deployment alternatives for parallel and distributed simulation systems

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dc.citation.epage18-24en_US
dc.citation.issueNumber3en_US
dc.citation.spage18-1en_US
dc.citation.volumeNumber23en_US
dc.contributor.authorÇelik, T.en_US
dc.contributor.authorTekinerdogan, B.en_US
dc.contributor.authorImre, K.en_US
dc.date.accessioned2015-07-28T12:01:13Z
dc.date.available2015-07-28T12:01:13Z
dc.date.issued2013-07en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractParallel and distributed simulations (PADS) realize the distributed execution of a simulation system over multiple physical resources. To realize the execution of PADS, different simulation infrastructures such as HLA, DIS and TENA have been defined. Recently, the Distributed Simulation Engineering and Execution Process (DSEEP) that supports the mapping of the simulations on the infrastructures has been defined. An important recommended task in DSEEP is the evaluation of the performance of the simulation systems at the design phase. In general, the performance of a simulation is largely influenced by the allocation of member applications to the resources. Usually, the deployment of the applications to the resources can be done in many different ways. DSEEP does not provide a concrete approach for evaluating the deployment alternatives. Moreover, current approaches that can be used for realizing various DSEEP activities do not yet provide adequate support for this purpose. We provide a concrete approach for deriving feasible deployment alternatives based on the simulation system and the available resources. In the approach, first the simulation components and the resources are designed. The design is used to define alternative execution configurations, and based on the design and the execution configuration; a feasible deployment alternative can be algorithmically derived. Tool support is developed for the simulation design, the execution configuration definition and the automatic generation of feasible deployment alternatives. The approach has been applied within a large-scale industrial case study for simulating Electronic Warfare systems. © 2013 ACM.en_US
dc.identifier.doi10.1145/2499913.2499917en_US
dc.identifier.eissn1558-1195
dc.identifier.issn1049-3301
dc.identifier.urihttp://hdl.handle.net/11693/12384
dc.language.isoEnglishen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/2499913.2499917en_US
dc.source.titleACM Transactions on Modeling and Computer Simulationen_US
dc.subjectAlgorithmsen_US
dc.subjectDesignen_US
dc.subjectPerformanceen_US
dc.subjectParallel and distributed simulationsen_US
dc.subjectHigh - level architectureen_US
dc.subjectDseepen_US
dc.subjectSoftware architectureen_US
dc.subjectModel transformationsen_US
dc.subjectMetamodelingen_US
dc.titleDeriving feasible deployment alternatives for parallel and distributed simulation systemsen_US
dc.typeArticleen_US

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