Performance Evaluation

Top Research Topics at Performance Evaluation?

Performance Evaluation primarily tackles Computer network, Queue, Queueing theory, Mathematical optimization and Distributed computing. It features studies on Computer network, including topics such as Network packet. The studies on Queue discussed can also contribute to research in the domains of Real-time computing and Server.

The Queueing theory study tackled is a key component of adjacent topics in the area of Algorithm. Mathematical optimization and Markov chain are closely related fields of research discussed in the journal.

• Computer network (11.93%)
• Queue (9.81%)
• Queueing theory (9.56%)

What are the most cited papers published in the journal?

• On the complexity of fixed-priority scheduling of periodic, real-time tasks (1016 citations)
• The Markov-modulated Poisson process (MMPP) cookbook (757 citations)
• Queueing analysis: A foundation of performance evaluation: Hideaki Takagi, vol. I: Vacation and priority systems, part I (1991), xii + 488 pp., ISBN 0-444-88910-8, Vol. II: Finite systems (1993), 560 pp., ISBN 0-444-81614-3, Vol. III: Discrete-time systems (1993), 484 pp., ISBN 0-444-81611-9, North-Holland, Amsterdam (622 citations)

Research areas of the most cited articles at Performance Evaluation:

The journal publications investigate areas of study like Computer network, Distributed computing, Real-time computing, Queue and Queueing theory. The study of Queue in the most cited papers encompasses disciplines such as Mathematical optimization, as well as fields such as Markov chain and Computation, all of which overlap with one another. Issues in Queueing theory were discussed in the journal articles, taking into consideration concepts from other disciplines like Algorithm and Simulation.

What topics the last edition of the journal is best known for?

• World War II
• Law
• Computer network

The previous edition focused in particular on these issues:

Performance Evaluation focuses on Cretaceous, Zoology, Genus, Paleontology and Process (engineering). While Performance Evaluation focused on Cretaceous, it was also able to explore topics like Mesozoic and Burmese. Zoology research is concerned with Baltic amber in particular.

Permian and Outcrop are all aspects of Paleontology research featured in the journal.

The most cited articles from the last journal are:

• Supplement to the Burmese (Myanmar) amber checklist and bibliography, 2020 (16 citations)
• Scalable load balancing in the presence of heterogeneous servers (6 citations)
• Optimal multiserver scheduling with unknown job sizes in heavy traffic (3 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Performance Evaluation (based on the number of publications) are:

• Diying Huang (53 papers) published 12 papers at the last edition, 6 less than at the previous edition,
• Herwig Bruneel (29 papers) absent at the last edition,
• Chenyang Cai (28 papers) published 8 papers at the last edition, 1 less than at the previous edition,
• Sławomir Dorocki (28 papers) absent at the last edition,
• Dany Azar (28 papers) published 7 papers at the last edition, 2 less than at the previous edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Performance Evaluation (based on the number of publications) are:

• Chinese Academy of Sciences (96 papers) published 23 papers at the last edition, 9 less than at the previous edition,
• IBM (87 papers) absent at the last edition,
• French Institute for Research in Computer Science and Automation (56 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Eindhoven University of Technology (53 papers) published 5 papers at the last edition, 4 more than at the previous edition,
• Imperial College London (48 papers) absent at the last edition.

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.

Publication chance based on affiliation

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 2021 edition, 37.28% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 23.78% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.79% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.29% of all publications and 53.15% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Educational Pathways into Performance Evaluation

For those interested in pursuing a career in the exciting field of Performance Evaluation and contributing to the important topics the journal handles, such as Computer network, Queue, Queueing theory, Mathematical optimization, and Distributed Computing, obtaining a relevant education is a critical first step.

Typically, prospective Performance Evaluators tend to major in Computer Science, Mathematics, Information Systems, or related fields at undergraduate levels. Pursuing further studies like a Master's or a Ph.D. in these areas often provides a sturdy theoretical foundation for a career in Performance Evaluation. This advanced education often involves intensive research, which stands aspiring Performance Evaluators in good stead, as research forms the cornerstone of this field.

In parallel to formal education, interested individuals can take additional steps to deepen their domain knowledge. This might include attending related courses or workshops, engaging in targeted reading and analysis of pertinent research papers, and staying abreast of emerging trends and developments in Performance Evaluation.

When making decisions regarding your educational and career path, it can be helpful to understand the requirements and responsibilities in similar roles. For instance, consider exploring how to become a middle school math teacher in New Jersey for insights into a related education-focused role.

Investing in the right education and making strategic career decisions can help pave the way for a rewarding career in Performance Evaluation, contributing to the growth and elevation of the field.