{"title":"基于云的仿真:最先进的计算机仿真范式","authors":"Xiaocheng Liu, X. Qiu, Bin Chen, Kedi Huang","doi":"10.1109/PADS.2012.11","DOIUrl":null,"url":null,"abstract":"The cloud computing paradigm attracts increasing amount of Modeling&Simulation (M&S) practitioners to perform their simulations in the cloud. Two issues, namely, the architecture of the Cloud-based Simulation (CSim) and the parallel simulation job scheduling in the CSim, should be addressed ï¬rst to make the CSim practical. This paper reports our recent work on the two issues. The architecture we proposed covers the software involved in the whole process of M&S by providing the Modeling as a Service (MaaS), the Execution as a Service (EaaS) and the Analysis as a Service (AaaS). The architecture also encourages the reuse of available simulation resources with the aid of the Simulation Resource as a Service (SRaaS). For the issue of parallel simulation job scheduling in the CSim, we ï¬rst propose a two-tier processor partition method to organize virtual machines (VMs) for parallel simulation workload consolidation, the two-tier VMs have different CPU priority. We then present four scheduling algorithms under such a partition method to cope with four common situations. Our extensive experiments on well-known traces show that all the four algorithms signiï¬cantly outperform their competitors.","PeriodicalId":299627,"journal":{"name":"2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation","volume":"234 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Cloud-Based Simulation: The State-of-the-Art Computer Simulation Paradigm\",\"authors\":\"Xiaocheng Liu, X. Qiu, Bin Chen, Kedi Huang\",\"doi\":\"10.1109/PADS.2012.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The cloud computing paradigm attracts increasing amount of Modeling&Simulation (M&S) practitioners to perform their simulations in the cloud. Two issues, namely, the architecture of the Cloud-based Simulation (CSim) and the parallel simulation job scheduling in the CSim, should be addressed ï¬rst to make the CSim practical. This paper reports our recent work on the two issues. The architecture we proposed covers the software involved in the whole process of M&S by providing the Modeling as a Service (MaaS), the Execution as a Service (EaaS) and the Analysis as a Service (AaaS). The architecture also encourages the reuse of available simulation resources with the aid of the Simulation Resource as a Service (SRaaS). For the issue of parallel simulation job scheduling in the CSim, we ï¬rst propose a two-tier processor partition method to organize virtual machines (VMs) for parallel simulation workload consolidation, the two-tier VMs have different CPU priority. We then present four scheduling algorithms under such a partition method to cope with four common situations. Our extensive experiments on well-known traces show that all the four algorithms signiï¬cantly outperform their competitors.\",\"PeriodicalId\":299627,\"journal\":{\"name\":\"2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation\",\"volume\":\"234 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PADS.2012.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PADS.2012.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cloud-Based Simulation: The State-of-the-Art Computer Simulation Paradigm
The cloud computing paradigm attracts increasing amount of Modeling&Simulation (M&S) practitioners to perform their simulations in the cloud. Two issues, namely, the architecture of the Cloud-based Simulation (CSim) and the parallel simulation job scheduling in the CSim, should be addressed ï¬rst to make the CSim practical. This paper reports our recent work on the two issues. The architecture we proposed covers the software involved in the whole process of M&S by providing the Modeling as a Service (MaaS), the Execution as a Service (EaaS) and the Analysis as a Service (AaaS). The architecture also encourages the reuse of available simulation resources with the aid of the Simulation Resource as a Service (SRaaS). For the issue of parallel simulation job scheduling in the CSim, we ï¬rst propose a two-tier processor partition method to organize virtual machines (VMs) for parallel simulation workload consolidation, the two-tier VMs have different CPU priority. We then present four scheduling algorithms under such a partition method to cope with four common situations. Our extensive experiments on well-known traces show that all the four algorithms signiï¬cantly outperform their competitors.