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Amir Behroozi

dblp:13/3387 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 100%
Software engineering, system software, and programming languages
1 paper
Services computing and microservices · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation › queueing models › queueing network model
layered queueing networks
0.012003
A performance model for a BPI middleware · EC 2003
Performance modeling and evaluation
queueing models
0.012003
A performance model for a BPI middleware · EC 2003

Methods — techniques the papers use, named apart from their topics

layered queueing network · 0.1
YearPublicationVenuePosition
2003 A performance model for a BPI middleware
abstract
With today's fast changing business environment and distributed global organizations, business processes of enterprises need to be able to quickly adapt to the new business requirements. BPI middlewares are thus developed to facilitate the integration of various types of enterprise applications that operate within or across enterprise boundaries. Due to the varying complexity and distributed nature of the business processes and the wide range of enterprise applications' characteristics, capacity planning and performance tuning of BPI middleware has been a challenge for engineers who develop and deploy BPI solutions. This poster presents a layered queueing network-based performance model for a BPI middleware to address this challenge.
Te-Kai Liu, Amir Behroozi, Santhosh Kumaran
EC2