With the wide use of commercial off-the-shelf (COTS) simulation packages and the advent of the high level architecture (HLA) standard which supports interoperability and reusability, it is desirable to build distributed simulations by linking various types of simulation models developed using best-fit COTS packages. While almost all current work on integrating COTS packages and the HLA is based on conservative synchronization, it is worthwhile to investigate the optimistic synchronization approach. The optimistic approach can exploit parallelism and achieve promising performance in situations where causality errors may occur but in fact seldom occur. In our paper, we introduce a rollback controller using a middleware approach to handle the complex rollback procedure on behalf of the simulation model. To fully utilize the benefits of optimistic synchronization, we also introduce a novel time advance algorithm using the services provided by the HLA. A comparison of performance between the conservative and optimistic synchronization approaches based on a typical reference model is also provided.
{"title":"Optimistic synchronization in HLA based distributed simulation","authors":"Xiaoguang Wang, S. Turner, M. Low, Boon-Ping Gan","doi":"10.1145/1013329.1013350","DOIUrl":"https://doi.org/10.1145/1013329.1013350","url":null,"abstract":"With the wide use of commercial off-the-shelf (COTS) simulation packages and the advent of the high level architecture (HLA) standard which supports interoperability and reusability, it is desirable to build distributed simulations by linking various types of simulation models developed using best-fit COTS packages. While almost all current work on integrating COTS packages and the HLA is based on conservative synchronization, it is worthwhile to investigate the optimistic synchronization approach. The optimistic approach can exploit parallelism and achieve promising performance in situations where causality errors may occur but in fact seldom occur. In our paper, we introduce a rollback controller using a middleware approach to handle the complex rollback procedure on behalf of the simulation model. To fully utilize the benefits of optimistic synchronization, we also introduce a novel time advance algorithm using the services provided by the HLA. A comparison of performance between the conservative and optimistic synchronization approaches based on a typical reference model is also provided.","PeriodicalId":326595,"journal":{"name":"18th Workshop on Parallel and Distributed Simulation, 2004. PADS 2004.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126393712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper advocates the use of a formal framework for analyzing simulation performance. Simulation performance is characterized based on the three simulation development process boundaries: physical system, simulation model, and simulator implementation. Firstly, we formalize simulation event ordering using partially ordered set theory. A simulator implements a simulation event ordering, and incurs implementation overheads when enforcing event ordering at runtime. Secondly, we apply our formalism to extract and formalize the simulation event orderings of both sequential and parallel simulations. Thirdly, we propose the relation stricter and a measure called strictness for comparing and quantifying the degree of event dependency of simulation event orderings respectively.
{"title":"Formalization and strictness of simulation event orderings","authors":"Y. M. Teo, B. Onggo","doi":"10.1145/1013329.1013345","DOIUrl":"https://doi.org/10.1145/1013329.1013345","url":null,"abstract":"This paper advocates the use of a formal framework for analyzing simulation performance. Simulation performance is characterized based on the three simulation development process boundaries: physical system, simulation model, and simulator implementation. Firstly, we formalize simulation event ordering using partially ordered set theory. A simulator implements a simulation event ordering, and incurs implementation overheads when enforcing event ordering at runtime. Secondly, we apply our formalism to extract and formalize the simulation event orderings of both sequential and parallel simulations. Thirdly, we propose the relation stricter and a measure called strictness for comparing and quantifying the degree of event dependency of simulation event orderings respectively.","PeriodicalId":326595,"journal":{"name":"18th Workshop on Parallel and Distributed Simulation, 2004. PADS 2004.","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121316946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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