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A Multi-Layered Scheme for Distributed Simulations on the Cloud Environment

机译:云环境下分布式仿真的多层方案

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In order to improve simulation performance and to integrate simulation resources among geographically distributed locations, the concept of distributed simulation is proposed. Several types of distributed simulation standards, such as DIS and HLA, are established to formalize simulations and achieve reusability and interoperability of simulation components. To implement these distributed simulation standards and to manage the underlying system of distributed simulation applications, we employ grid computing and cloud computing technologies. These tackle the details of operation, configuration, and maintenance of simulation platforms in which simulation applications are deployed. However, for modelers who may not be familiar with the management of distributed systems, it is challenging to make a simulation-run-ready environment among different types of computing resources and network environments. In this article, a new multi-layered cloud-based scheme is proposed for enabling modeling and simulation based on different distributed simulation standards. This scheme is designed to ease the management of underlying resources and to achieve rapid elasticity that can provide unlimited computing capability to end users; it considers energy consumption, security, multi-user availability, scalability, and deployment issues. A mechanism for handling diverse network environments is described; by adopting it, idle public resources can be easily configured as additional computing capabilities for the local resource pool. A fast deployment model is built to relieve the migration and installation process of this platform. An energy-saving strategy is utilized to reduce the consumption of computing resources. Security components are implemented to protect sensitive information and block malicious attacks in the cloud. In the experiments, the proposed scheme is compared with its corresponding grid computing platform; the cloud computing platform achieves similar performance, but incorporates many advantages that the Cloud can provide.
机译:为了提高仿真性能,并在地理位置上整合仿真资源,提出了分布式仿真的概念。建立了几种类型的分布式仿真标准,例如DIS和HLA,以使仿真形式化并实现仿真组件的可重用性和互操作性。为了实现这些分布式仿真标准并管理分布式仿真应用程序的基础系统,我们采用了网格计算和云计算技术。这些解决了部署模拟应用程序的模拟平台的操作,配置和维护的细节。但是,对于可能不熟悉分布式系统管理的建模人员而言,在不同类型的计算资源和网络环境之间创建一个可运行模拟的环境是一项挑战。在本文中,提出了一种新的基于云的多层方案,用于基于不同的分布式仿真标准进行建模和仿真。此方案旨在简化基础资源的管理并实现快速弹性,从而可以为最终用户提供无限的计算能力;它考虑了能耗,安全性,多用户可用性,可伸缩性和部署问题。描述了一种用于处理各种网络环境的机制。通过采用它,闲置的公共资源可以轻松地配置为本地资源池的其他计算功能。建立了快速部署模型以减轻该平台的迁移和安装过程。利用节能策略来减少计算资源的消耗。实施安全组件可保护敏感信息并阻止云中的恶意攻击。在实验中,将该方案与相应的网格计算平台进行了比较;云计算平台可实现类似的性能,但具有云可提供的许多优势。

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