A simulation as a service cloud middleware

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• 作者：Shashank Shekhar ; Hamzah Abdel-Aziz ; Michael Walker…
• 关键词：Cloud computing ; Middleware ; Linux container ; Simulation ; as ; a ; Service
• 刊名：Annals of Telecommunications
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：71
• 期：3-4
• 页码：93-108
• 全文大小：2,890 KB
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• 作者单位：Shashank Shekhar (1)
  Hamzah Abdel-Aziz (1)
  Michael Walker (1)
  Faruk Caglar (1)
  Aniruddha Gokhale (1)
  Xenofon Koutsoukos (1)
  
  1. Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, 37235, USA
  
• 刊物类别：Engineering
• 刊物主题：Engineering, general
  Electronic and Computer Engineering
  
• 出版者：Springer Paris
• ISSN：1958-9395

文摘

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.