Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration

There are many challenges in measuring capacity using metrics such as transactions per minute (TPM) and operation per second (OPS) for all server hardware, which are becoming increasingly obsolete due to the shortening of the lifecycle of hardware and the advent of microprocessors. Instead, the resu...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Hun Joe, Sungjin Kim, Brent Byunghoon Kang
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Server sizing capacity planning Unix to Linux (U2L) migration Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/14e32aa3eb0f46df9ae57cf62c4adfdc
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:14e32aa3eb0f46df9ae57cf62c4adfdc
record_format	dspace
spelling	oai:doaj.org-article:14e32aa3eb0f46df9ae57cf62c4adfdc2021-11-04T23:00:56ZQuantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration2169-353610.1109/ACCESS.2021.3119397https://doaj.org/article/14e32aa3eb0f46df9ae57cf62c4adfdc2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9567673/https://doaj.org/toc/2169-3536There are many challenges in measuring capacity using metrics such as transactions per minute (TPM) and operation per second (OPS) for all server hardware, which are becoming increasingly obsolete due to the shortening of the lifecycle of hardware and the advent of microprocessors. Instead, the results of accredited performance measurements are used to measure these standards, which are further used as references in the capacity measuring methods employed by industries. Generally, in industries, the capacity of a web application server is defined by OPS, for which no clear transition criterion exists for calculating tpmC using an empirical verification method. Considering secure Unix to Linux (U2L) x86-based server migration, there are no methods to compare and verify the max-jOPS value of Standard Performance Evaluation Corp., which is an industry-recognized performance measurement standard, to the Unix-based benchmark tpmC. In this study, a scenario-based U2L migration was empirically verified by analyzing and comparing pre-to-post with the interpretation of a census statistical system log data, which was conducted on approximately 1.7M households over 21 days with 25,288 maximum concurrent users. We present the correlation through pre-to-post comparison and analysis of U2L for each census statistical system log data by measuring the maximum CPU utilization as U2L migration between heterogeneous CPUs. The correlation is applied to OPS using the tpmC value of TPC-C proportional equation and quantified as a derived conversion ratio of OPS to max-jOPS. Consequently, we formulated and normalized an arithmetic expression, resulting in a CPU core conversion ratio of 0.165 as facile from a Unix-based legacy platform to an x86-based server. Therefore, we propose a new server sizing model for secure U2L migration between heterogeneous CPU architectures, which results in an average of 14.3% improvement in data processing time.Hun JoeSungjin KimBrent Byunghoon KangIEEEarticleServer sizingcapacity planningUnix to Linux (U2L) migrationElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 142449-142460 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Server sizing capacity planning Unix to Linux (U2L) migration Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Server sizing capacity planning Unix to Linux (U2L) migration Electrical engineering. Electronics. Nuclear engineering TK1-9971 Hun Joe Sungjin Kim Brent Byunghoon Kang Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration
description	There are many challenges in measuring capacity using metrics such as transactions per minute (TPM) and operation per second (OPS) for all server hardware, which are becoming increasingly obsolete due to the shortening of the lifecycle of hardware and the advent of microprocessors. Instead, the results of accredited performance measurements are used to measure these standards, which are further used as references in the capacity measuring methods employed by industries. Generally, in industries, the capacity of a web application server is defined by OPS, for which no clear transition criterion exists for calculating tpmC using an empirical verification method. Considering secure Unix to Linux (U2L) x86-based server migration, there are no methods to compare and verify the max-jOPS value of Standard Performance Evaluation Corp., which is an industry-recognized performance measurement standard, to the Unix-based benchmark tpmC. In this study, a scenario-based U2L migration was empirically verified by analyzing and comparing pre-to-post with the interpretation of a census statistical system log data, which was conducted on approximately 1.7M households over 21 days with 25,288 maximum concurrent users. We present the correlation through pre-to-post comparison and analysis of U2L for each census statistical system log data by measuring the maximum CPU utilization as U2L migration between heterogeneous CPUs. The correlation is applied to OPS using the tpmC value of TPC-C proportional equation and quantified as a derived conversion ratio of OPS to max-jOPS. Consequently, we formulated and normalized an arithmetic expression, resulting in a CPU core conversion ratio of 0.165 as facile from a Unix-based legacy platform to an x86-based server. Therefore, we propose a new server sizing model for secure U2L migration between heterogeneous CPU architectures, which results in an average of 14.3% improvement in data processing time.
format	article
author	Hun Joe Sungjin Kim Brent Byunghoon Kang
author_facet	Hun Joe Sungjin Kim Brent Byunghoon Kang
author_sort	Hun Joe
title	Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration
title_short	Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration
title_full	Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration
title_fullStr	Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration
title_full_unstemmed	Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration
title_sort	quantitative server sizing model for performance satisfaction in secure u2l migration
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/14e32aa3eb0f46df9ae57cf62c4adfdc
work_keys_str_mv	AT hunjoe quantitativeserversizingmodelforperformancesatisfactioninsecureu2lmigration AT sungjinkim quantitativeserversizingmodelforperformancesatisfactioninsecureu2lmigration AT brentbyunghoonkang quantitativeserversizingmodelforperformancesatisfactioninsecureu2lmigration
_version_	1718444574326652928

Quantitative Server Sizing Model for Performance Satisfaction in Secure U2L Migration

Ejemplares similares