CLOURA: CLOUD Risk Assessor (with Stochastic & Non-Stochastic Simulations) | Zendy

Mehmet Şahinoglu | Zendy

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CLOURA: CLOUD Risk Assessor (with Stochastic & Non-Stochastic Simulations)

Author(s) -

Mehmet Şahinoglu

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.08.402

Subject(s) - cloud computing , computer science , scalability , desk , scope (computer science) , wizard , discrete event simulation , server , event (particle physics) , markov chain , simulation , operations research , distributed computing , database , operating system , physics , quantum mechanics , engineering , programming language , machine learning

The speaker will explain in detail, regarding the “CLOUD Simulation” tool (CLOURA). In comparison to other alternatives, scalable CLOURA comparatively is faster, i.e. it can simulate a CLOUD system such as with 443 servers and load demand of 8760hours or 1000 years in <4minutes and 10,000 years in 40minutes covering many billions of calculations. SOCIAL CLOUD version to serve HUMAN RESOURCES data to prejudge performance risk will also be covered. A discrete event CLOUD simulator, CLOURA, is hereby examined to estimate the risk indices in large CLOUD computing environments, comparing favorably with the intractably tedious theoretical Markov solutions limited in scope. The details of input (wizard) and output specs will be explained in the Help Desk of the software. Cost related risk mitigation can be conducted for how many to invest for i) reserve repair crews, and ii) adding products

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