Evaluating Cloud Auto-Scaler Resource Allocation Planning Under High-Performance Computing Workloads

Leochico, Kester; John, Eugene

doi:10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00147

2020 IEEE Intl Conf on Parallel &Amp; Distributed Processing With Applications, Big Data &Amp; Cloud Computing, Sustainable Com 2020

DOI: 10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00147

|View full text |Cite

Evaluating Cloud Auto-Scaler Resource Allocation Planning Under High-Performance Computing Workloads

Kester Leochico

Eugene John

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Mathematical Modelling and Study of Stochastic Parameters of Computer Data Processing

Romansky

2021

Mathematics

View full text Add to dashboard Cite

The main goal of dispatching strategies is to minimize the total time for processing tasks at maximum performance of the computer system, which requires strict regulation of the workload of the processing units. To achieve this, it is necessary to conduct a preliminary study of the applied model for planning. The purpose of this article is to present an approach for automating the investigation and optimization of processes in a computer environment for task planning and processing. A stochastic input flow of incoming tasks for processing is considered and mathematical formalization of some probabilistic characteristics related to the complexity of its servicing has been made. On this basis, a software module by using program language APL2 has been developed to conduct experiments for analytical study and obtaining estimates of stochastic parameters of computer processing and dispatching. The proposed model is part of a generalized environment for program investigation of the computer processing organization and expands its field of application with additional research possibilities.

show abstract

Mathematical Modelling and Study of Stochastic Parameters of Computer Data Processing

Romansky

2021

Mathematics

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Evaluating Cloud Auto-Scaler Resource Allocation Planning Under High-Performance Computing Workloads

Cited by 1 publication

References 11 publications

Mathematical Modelling and Study of Stochastic Parameters of Computer Data Processing

Mathematical Modelling and Study of Stochastic Parameters of Computer Data Processing

Contact Info

Product

Resources

About