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Khaled Almakadmeh

dblp:08/11109 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0001-5811-1975ORCID · corroborated

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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
Distributed systems · 100%

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

TopicWeightPapersLastEvidence papers
Distributed systems › grid computing
data grid
0.212016
A Round-based Data Replication Strategy · IEEE Trans. Parallel Distributed Syst. 2016
Distributed systems › replication
data replication
0.212016
A Round-based Data Replication Strategy · IEEE Trans. Parallel Distributed Syst. 2016
Distributed systems › replication › replica management
replica selection
0.112016
A Round-based Data Replication Strategy · IEEE Trans. Parallel Distributed Syst. 2016

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

simulation · 0.2
YearPublicationVenuePosition
2016 A Round-based Data Replication Strategy
abstract
Data Grid allows many organizations to share data across large geographical area. The idea behind data replication is to store copies of the same file at different locations. Therefore, if a copy at a location is lost or not available, it can be brought from another location. Additionally, data replication results in a reduced time and bandwidth because of bringing the file from a closer location. However, the files that need to be replicated have to be selected wisely. In this paper, a round-based data replication strategy is proposed to select the most appropriate files for replication at the end of each round based on a number of factors. The proposed strategy is based on Popular File Replicate First (PFRF) strategy, and it overcomes the drawbacks of PFRF. The simulation results show that the proposed strategy yields better performance in terms of average file delay per request, average file bandwidth consumption per request, and percentage of files found.
Mohammad Bsoul, Alaa Eddien Abdallah, Khaled Almakadmeh, Nedal Tahat
IEEE Trans. Parallel Distributed Syst.3
2012 A finite mixture model for simultaneous high-dimensional clustering, localized feature selection and outlier rejection
Nizar Bouguila, Khaled Almakadmeh, Sabri Boutemedjet
Expert Syst. Appl.2