CCMA—cloud critical metric assessment framework for scientific computing

Ravindhren, V.G.; Ravimaran, S.

doi:10.1007/s10586-017-1384-4

Cited by 5 publications

(2 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in Figure 1, the smart campus integrates teaching, research, and management based on the digital campus. Based on mobile Internet and intelligent sensing network and supported by big data and cloud computing [19,20], the gap between the virtual campus and the physical campus is narrowing, and the activities of school teachers and students have covered the old physical space and the emerging digital space. Campus security, on-campus management, teacher and student classrooms, learning modes, teaching methods, and office processes will all be gradually made smart.…”

Section: Exploration Of Higher Education Under Cloud Computing and Bi...mentioning

confidence: 99%

Big Data Analysis and Modeling of Higher Education Reform Based on Cloud Computing Technology

Tang

2022

Security and Communication Networks

View full text Add to dashboard Cite

In view of the current educational environment, the development of higher education cannot be separated from the support of information technology. The era of big data has had various impacts on higher education and accelerated the development of higher education. Cloud computing technology has good application prospects for the data analysis and mathematical modeling content involved in the reform of higher education. This study analyzes and calculates the concerns of the four main contents involved in the educational reform of a higher education institution as the research object. In order to quantify the application effects of different cloud computing technologies, the paper introduces three typical cloud computing technologies to analyze the research data and establish related mathematical models. The results show that the prediction accuracy based on the immune cloning algorithm is the best. Based on the calculation results, it can be found that the corresponding data of the two main contents of teaching scene setting and teaching quality detection show an obvious polynomial function relationship.

show abstract

Section: Exploration Of Higher Education Under Cloud Computing and Bi...mentioning

confidence: 99%

Big Data Analysis and Modeling of Higher Education Reform Based on Cloud Computing Technology

Tang

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…This paradigm allows on demand virtualized resource provisioning under a pay-per-use business model without upfront investment [47], where resources can be reserved and released without human intervention through user defined scalability rules [46], yielding virtually infinite scalability of an application at reasonable costs [53]. Though this fact makes cloud computing very appealing for scientific, performance-demanding applications [41], such as simulators, the usage of cloud computing in the educational realm is very much limited to ready Software-asa-Service applications [22,44]. This paper leverages the flexible scalability and cost model of the cloud to propose DNSE3 (Distributed Network Simulation Environment 3), an application conceived for education that allows students to define, run and analyze both single simulations and parameter sweeps.…”

Section: Manuscript Main Source Filementioning

confidence: 99%

A self-scalable distributed network simulation environment based on cloud computing

et al. 2018

View full text Add to dashboard Cite

While parameter sweep simulations can help undergraduate students and researchers to understand computer networks, their usage in the academia is hindered by the significant computational load they convey. This paper proposes DNSE3, a service oriented computer network simulator that, deployed in a cloud computing infrastructure, leverages its elasticity and pay-per-use features to compute parameter sweeps. The performance and cost of using this application is evaluated in several experiments applying different scalability policies, with results that meet the demands of users in educational institutions. Additionally, the usability of the application has been measured following industry standards with real students, yielding a very satisfactory user experience.

show abstract

Response Surface Modelling for Performance Analysis of Scientific Workflow Application in Cloud

Prathibha

Latha

2020

Cluster Comput

View full text Add to dashboard Cite

CCMA—cloud critical metric assessment framework for scientific computing

Cited by 5 publications

References 24 publications

Big Data Analysis and Modeling of Higher Education Reform Based on Cloud Computing Technology

Big Data Analysis and Modeling of Higher Education Reform Based on Cloud Computing Technology

A self-scalable distributed network simulation environment based on cloud computing

Response Surface Modelling for Performance Analysis of Scientific Workflow Application in Cloud

Contact Info

Product

Resources

About