A generic cloud platform for engineering optimization based on OpenStack

Li, Zhaojun, Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133, Wang, Xicheng and Li, Keqiu 2014. A generic cloud platform for engineering optimization based on OpenStack. Advances in engineering software 75 , pp. 42-57. 10.1016/j.advengsoft.2014.05.001

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Abstract

Optimizations have been applied in many different engineering fields. Most of these applications may have similar characteristics: intensive on computing resources, time-consuming on calculation iterations, similar on computing environments and so on. This paper describes a generic cloud platform for engineering optimization by leveraging the compute resources hosted in cloud datacenters. The methodology developed was to decompose the engineering optimization processes into several interconnected sub-tasks, which were further converted and implemented as virtual applications for dynamic cloud deployment using OpenStack. The system can dynamically allocate and recycle the compute resources according to the specific engineering optimization applications. The research presented in the paper contributes on the generic engineering optimization process virtualization and cloud computing based implementation with innovative algorithms development. The system test results showed a way that potentially engineering optimization problems could be embedded into the put forward platform due to the developed large scale and intelligent cloud based optimization services. Further applications for building energy simulation and optimization, stents optimization, water distribution optimization are currently under development.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords:	Cloud computing; engineering optimization; OpenStack; optimization algorithm; high performance computing; scheduling algorithm.
Publisher:	Elsevier
ISSN:	0965-9978
Last Modified:	25 Oct 2022 09:58
URI:	https://orca.cardiff.ac.uk/id/eprint/60646

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