Deriving feasible deployment alternatives for parallel and distributed simulation systems
dc.citation.epage | 18-24 | en_US |
dc.citation.issueNumber | 3 | en_US |
dc.citation.spage | 18-1 | en_US |
dc.citation.volumeNumber | 23 | en_US |
dc.contributor.author | Çelik, T. | en_US |
dc.contributor.author | Tekinerdogan, B. | en_US |
dc.contributor.author | Imre, K. | en_US |
dc.date.accessioned | 2015-07-28T12:01:13Z | |
dc.date.available | 2015-07-28T12:01:13Z | |
dc.date.issued | 2013-07 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | Parallel 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.description.provenance | Made available in DSpace on 2015-07-28T12:01:13Z (GMT). No. of bitstreams: 1 10.1145-2499913.2499917.pdf: 1039856 bytes, checksum: 0344ff5408c0365ddded0f0b6876434c (MD5) | en |
dc.identifier.doi | 10.1145/2499913.2499917 | en_US |
dc.identifier.eissn | 1558-1195 | en_US |
dc.identifier.issn | 1049-3301 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/12384 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Association for Computing Machinery | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1145/2499913.2499917 | en_US |
dc.source.title | ACM Transactions on Modeling and Computer Simulation | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Design | en_US |
dc.subject | Performance | en_US |
dc.subject | Parallel and distributed simulations | en_US |
dc.subject | High - level architecture | en_US |
dc.subject | Dseep | en_US |
dc.subject | Software architecture | en_US |
dc.subject | Model transformations | en_US |
dc.subject | Metamodeling | en_US |
dc.title | Deriving feasible deployment alternatives for parallel and distributed simulation systems | en_US |
dc.type | Article | en_US |
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