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

In order to improve simulation performance and 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. In order to implement these distributed simulation standards and manage the underlying system of distributed simulation applications, Grid Computing and Cloud Computing technologies are employed to tackle the details of operation, configuration, and maintenance of the 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 create a simulation-run-ready environment that incorporates different types of computing resources and network environments. In this thesis, we propose a new multi-layered cloud-based scheme for enabling modeling and simulation based on different distributed simulation standards. The scheme is designed to ease the management of underlying resources and achieve rapid elasticity, providing unlimited computing capability to end users; energy consumption, security, multi-user availability, scalability and deployment issues are all considered. We describe a mechanism for handling diverse network environments. With its adoption, idle public resources can easily be 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 conservation strategy is utilized to reduce the energy consumption of computing resources. Security components are also 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 a similar performance, but incorporates many of the cloud's advantages.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/32121
Date January 2015
CreatorsGuan, Shichao
ContributorsAzzedine, Boukerche
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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