0743-7315
Published by: Elsevier
https://www.journals.elsevier.com/journal-of-parallel-and-distributed-computing
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 94 | 264 | 265 | 44 |
The aim of the journal is to expand the discussion of research in Parallel computing, Distributed computing, Algorithm, Parallel algorithm and Computer network. The work on Parallel computing addressed in the journal expands to the thematically related Computation. While work presented in Journal of Parallel and Distributed Computing provided substantial information on Distributed computing, it also covered topics in Scheduling (computing), Cloud computing and Scalability.
Fair-share scheduling and Dynamic priority scheduling are some of the study areas of Scheduling (computing) discussed. It connects research in Algorithm with the related topic of Theoretical computer science. It features Computer network research that overlaps with concepts in Wireless network.
Parallel computing, Distributed computing, Algorithm, Scheduling (computing) and Parallel algorithm are the main subjects of interest in the journal papers. The most cited papers explore research in Computer network and overlapping concepts in Wireless network to expand the discourse in Distributed computing. The featured Parallel algorithm studies in the published papers mainly concentrate on Graph but also cover areas of interest in Theoretical computer science.
The foci of Journal of Parallel and Distributed Computing are Scalability, Mathematical optimization, Server, Computational science and Speedup. Scalability research featured in the journal incorporates concerns from various other topics such as Deep learning, Artificial intelligence, Descent direction, Synchronization (computer science) and Central processing unit. It facilitates discussions on Mathematical optimization that incorporate concepts from other fields like Scheduling (computing), Computation offloading, Smart grid and Renewable energy.
While Server is the focus of the journal, it also provided insights into the studies of Iterative method, Cloud computing, Best response, Nash equilibrium and Computation. Journal of Parallel and Distributed Computing covers Speedup research under the subject of Parallel computing.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Parallel and Distributed Computing (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Parallel and Distributed Computing (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2022 edition, 20.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 25.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 25.00% of all publications and 50.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Parallel and distributed computing involves a wide range of study areas, opening doors to numerous career opportunities for those who wish to venture into this field. For instance, scholars who master the aspects of parallel computing, distributed computing, and algorithm could become software engineers, systems architects, or data scientists.
Furthermore, the understanding of theoretical computer science and knowledge in operating systems could lead one to develop a career as a computer systems analyst or computer network architect. The research in artificial intelligence presented in the journal also suggests opportunities in developing advanced intelligent systems, robotics, and machine learning applications.
It is important to note that the career path one chooses depends on their ambitions, skills, and education level. Higher education levels such as a master's or doctoral degree could lead to a successful career in academia or research. For instance, if you have ever wondered about a career in education, you might be interested in understanding how to become a preschool teacher in hawaii.
Besides traditional career paths, parallel and distributed computing skills could also lead to opportunities in upcoming fields like cloud computing, deep learning, computational science, and many more. Thus, continual learning is key in this ever-evolving field.
Gia Nhu Nguyen;Nin Ho Le Viet;Mohamed Elhoseny;Mohamed Elhoseny;K. Shankar
(2021)Unknown
(2022)Unknown
(2022)A. Francis Saviour Devaraj;Mohamed Elhoseny;S. Dhanasekaran;E. Laxmi Lydia
(2020)Unknown
(2022)Zisang Xu;Wei Liang;Kuan-Ching Li;Jianbo Xu
(2021)Yaser Mansouri;M. Ali Babar
(2021)Unknown
(2020)Aparna Kumari;Rajesh Gupta;Sudeep Tanwar;Neeraj Kumar;Neeraj Kumar;Neeraj Kumar
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