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IEEE Transactions on Computers
H-index 41

IEEE Transactions on Computers

0018-9340

Published by: IEEE

https://www.computer.org/web/tc

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 106 357 538 41

Additional Metrics

Number of Best Scientists*: 446
Documents by Best Scientists*: 611
Top 100 Ranked Scientists*: 9
SCIMAGO H-index: 145
SCIMAGO SJR: 1.156
Impact Factor: 3.8

Overview

Top Research Topics at IEEE Transactions on Computers?

IEEE Transactions on Computers primarily focuses on research topics in Algorithm, Parallel computing, Distributed computing, Discrete mathematics and Computer network. Algorithm research presented in the journal encompasses a variety of subjects, including Fault (power engineering), Fault detection and isolation, Theoretical computer science and Arithmetic. Parallel computing research discussed connects with the study of Very-large-scale integration.

The majority of Distributed computing studies are focused on the issues of Fault tolerance. It features Discrete mathematics research that overlaps with concepts in Combinatorics.

  • Algorithm (20.63%)
  • Parallel computing (16.64%)
  • Distributed computing (9.81%)

What are the most cited papers published in the journal?

  • Graph-Based Algorithms for Boolean Function Manipulation (7935 citations)
  • Discrete Cosine Transform (3755 citations)
  • The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver (3370 citations)

Research areas of the most cited articles at IEEE Transactions on Computers:

The journal papers primarily tackle Parallel computing, Algorithm, Distributed computing, Computer network and Fault tolerance. The works on Parallel computing tackled in the most cited articles bring together disciplines like Very-large-scale integration and Adder. The studies on Algorithm discussed at the journal publications can also contribute to research in the domains of Fault (power engineering), Fault detection and isolation, Theoretical computer science and Arithmetic.

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

  • Operating system
  • Artificial intelligence
  • Computer network

The previous edition focused in particular on these issues:

The objective of the journal is to combine knowledge in the areas of Distributed computing, Parallel computing, Artificial neural network, Embedded system and Artificial intelligence. The tackled Distributed computing research is interrelated with Overhead (computing) which concerns subjects like Memory management. Parallel computing research is the primary subject tackled in the journal with a focus on Speedup.

In addition to Artificial neural network research, it aims to explore topics under Efficient energy use and Computer engineering. Studies on Embedded system discussed in the journal link to the field of Energy consumption. The studies tackled, which mainly focus on Artificial intelligence, apply to Machine learning as well.

The most cited articles from the last journal are:

  • SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead (22 citations)
  • Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators (22 citations)
  • EIHDP: Edge-Intelligent Hierarchical Dynamic Pricing Based on Cloud-Edge-Client Collaboration for IoT Systems (19 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.

The top authors publishing in IEEE Transactions on Computers (based on the number of publications) are:

  • Kang G. Shin (52 papers) absent at the last edition,
  • Sudhakar M. Reddy (47 papers) absent at the last edition,
  • Irith Pomeranz (38 papers) absent at the last edition,
  • 홍대식 (35 papers) absent at the last edition,
  • Yuanyuan Yang (33 papers) published 1 paper at the last edition the same number as 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.

Only papers with recognized affiliations are considered

The top affiliations publishing in IEEE Transactions on Computers (based on the number of publications) are:

  • IBM (403 papers) published 4 papers at the last edition, 3 more than at the previous edition,
  • University of Illinois at Urbana–Champaign (240 papers) published 3 papers at the last edition, 2 more than at the previous edition,
  • Bell Labs (201 papers) absent at the last edition,
  • University of Southern California (173 papers) published 3 papers at the last edition, 1 more than at the previous edition,
  • University of Michigan (155 papers) published 1 paper at the last edition, 1 less than at the previous 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, 19.89% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 6.74% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.74% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.63% of all publications and 64.89% 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.

How to Contribute to IEEE Transactions on Computers

Diving into this prestigious realm of computer science research might seem daunting at first. Though it requires heavy preparation, the opportunity to contribute significantly to the targeted areas such as Algorithms, Parallel computing, Distributed computing, Discrete mathematics, and Computer network can be highly rewarding. Here, we will guide you on how to initiate your journey to contribute valuable research to IEEE Transactions on Computers. Firstly, you must understand that becoming a well-rounded researcher necessitates having a strong foundational knowledge in your respective domain. This foundation includes a comprehensive understanding of the fundamentals of computer science as well as a nuanced comprehension of specialized fields like Distributed computing and Parallel computing. You should also develop your research skills, especially those focused on critical problem-solving. Be familiar with the unique research methodologies and tools typically used in computer science research, such as statistical analysis techniques, simulation and modeling tools, and software development environments. Furthermore, contributing to IEEE Transactions on Computers involves drafting high-quality research papers. It requires strong writing capabilities, meaning one must be skillful at clearly describing complex technical concepts and expressing innovative ideas. A profound practice strategy can be deciding upon a focused area of interest and exploring related issues extensively. Read and scrutinize published research papers to understand their approaches, methodologies, results, and modes of effective communication. Keep abreast of the most recent research topics and the associated theoretical frameworks and methodologies. Finally, another vital element to consider is the collaborative nature of research. Foster relationships with professors, fellow students, and researchers to widen your academic insights and gain fresh perspectives. Collaboration often leads to well-rounded research and may open doors to exciting opportunities. Deciding to become a researcher requires a significant commitment of time and effort in the specialized area of computer science, similar to how how long it takes to become a middle school math teacher in Hawaii. Research is a journey filled with constant learning and discovery. The patience and perseverance instilled along this path serve as stepping stones to making substantial contributions to the scientific community. Remember, your research could potentially influence the thinking of future computer science enthusiasts and pave the way for noteworthy advancements in this field. Begin your journey today, and who knows? Your research paper could be the next most cited on IEEE Transactions on Computers!

Top Publications

  • SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead

    Wentai Wu;Ligang He;Weiwei Lin;Rui Mao

    (2021)
    239 Citations
  • Dependent Task Offloading for Edge Computing based on Deep Reinforcement Learning

    Jin Wang;Jia Hu;Geyong Min;Wenhan Zhan

    (2021)
    223 Citations
  • A Deep Reinforcement Learning Based Offloading Game in Edge Computing

    Yufeng Zhan;Song Guo;Peng Li;Jiang Zhang

    (2020)
    146 Citations
  • EIHDP: Edge-Intelligent Hierarchical Dynamic Pricing Based on Cloud-Edge-Client Collaboration for IoT Systems

    Tian Wang;Yucheng Lu;Jianhuang Wang;Hong-Ning Dai

    (2021)
    138 Citations
  • Efficient CP-ABE Scheme with Shared Decryption in Cloud Storage

    Ningyu Chen;Jiguo Li;Yichen Zhang;Yuyan Guo

    (2020)
    134 Citations
  • Adaptive Federated Learning on Non-IID Data with Resource Constraint

    Jie Zhang;Song Guo;Zhihao Qu;Deze Zeng

    (2021)
    124 Citations
  • Hardware Private Circuits: From Trivial Composition to Full Verification

    Gaetan Cassiers;Benjamin Gregoire;Itamar Levi;Francois-Xavier Standaert

    (2021)
    114 Citations
  • A Blockchain-Based Decentralized, Fair and Authenticated Information Sharing Scheme in Zero Trust Internet-of-Things

    (2023)
    93 Citations
  • DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs

    Alessio Burrello;Angelo Garofalo;Nazareno Bruschi;Giuseppe Tagliavini

    (2021)
    92 Citations
  • Grow and Prune Compact, Fast, and Accurate LSTMs

    Xiaoliang Dai;Hongxu Yin;Niraj K. Jha

    (2020)
    89 Citations

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Best Scientists Contributing to This Journal