IEEE Transactions on Network Science and Engineering

Top Research Topics at IEEE Transactions on Network Science and Engineering?

Computer network, Distributed computing, Artificial intelligence, Mathematical optimization and Complex network are among the topics commonly tackled in IEEE Transactions on Network Science and Engineering. While it focused on Computer network, it was also able to explore topics like Wireless and Wireless network. Topics in Distributed computing explored in IEEE Transactions on Network Science and Engineering were investigated in conjunction with research in Enhanced Data Rates for GSM Evolution, Edge computing and Server.

It focuses on Artificial intelligence research which is adjacent to topics in Machine learning. Research on Complex network addressed in IEEE Transactions on Network Science and Engineering frequently intersections with the field of Topology.

• Computer network (14.88%)
• Distributed computing (12.75%)
• Artificial intelligence (9.50%)

What are the most cited papers published in the journal?

• A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems (190 citations)
• Random Walks, Markov Processes and the Multiscale Modular Organization of Complex Networks (165 citations)
• Spreading Processes in Multilayer Networks (152 citations)

Research areas of the most cited articles at IEEE Transactions on Network Science and Engineering:

The most cited articles primarily focus on research topics in Distributed computing, Computer network, Random graph, Complex network and Theoretical computer science. The studies on Distributed computing discussed at the journal articles can also contribute to research in the domains of Resource allocation, Communication channel, Task analysis, Multiplexing and Reinforcement learning. While work presented in the most cited articles provide substantial information on Theoretical computer science, it also covers topics in Centrality, Approximation algorithm and Cluster analysis.

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

• Computer network
• Artificial intelligence
• The Internet

The previous edition focused in particular on these issues:

The foci of the journal are Computer network, Artificial intelligence, Distributed computing, Server and Computer security. The Computer network works featured in the journal incorporate elements from Wireless and Wireless network. It facilitates discussions on Artificial intelligence that incorporate concepts from other fields like Data modeling and Machine learning.

The studies on Distributed computing discussed can also contribute to research in the domains of Mobile device and Reinforcement learning. The work tackled in IEEE Transactions on Network Science and Engineering goes beyond the discipline of Server as it also encompasses Enhanced Data Rates for GSM Evolution. Studies on Computer security discussed in IEEE Transactions on Network Science and Engineering link to the field of The Internet.

The most cited articles from the last journal are:

• BinDaaS: Blockchain-Based Deep-Learning as-a-Service in Healthcare 4.0 Applications (48 citations)
• B-Ride: Ride Sharing With Privacy-Preservation, Trust and Fair Payment Atop Public Blockchain (46 citations)
• Privacy-Aware Cross-Platform Service Recommendation Based on Enhanced Locality-Sensitive Hashing (45 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 IEEE Transactions on Network Science and Engineering (based on the number of publications) are:

• Tingwen Huang (16 papers) published 4 papers at the last edition, 4 less than at the previous edition,
• Naixue Xiong (15 papers) published 13 papers at the last edition, 11 more than at the previous edition,
• Jie Wu (12 papers) published 5 papers at the last edition the same number as at the previous edition,
• Laurence T. Yang (12 papers) published 9 papers at the last edition, 6 more than at the previous edition,
• Mohsen Guizani (11 papers) published 9 papers at the last edition, 7 more 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 IEEE Transactions on Network Science and Engineering (based on the number of publications) are:

• Huazhong University of Science and Technology (23 papers) published 17 papers at the last edition, 11 more than at the previous edition,
• Southeast University (22 papers) published 10 papers at the last edition, 1 less than at the previous edition,
• Temple University (20 papers) published 11 papers at the last edition, 4 more than at the previous edition,
• Shanghai Jiao Tong University (20 papers) published 7 papers at the last edition, 3 less than at the previous edition,
• Central South University (19 papers) published 15 papers at the last edition, 11 more 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, 15.85% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 27.90% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.87% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.48% of all publications and 42.75% 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.

Career Prospects in Network Science and Engineering

As you delve into the broad field of Network Science and Engineering, it's crucial to consider the possible career paths open to you. Given its inherently interdisciplinary nature, Network Science and Engineering careers can span several industries, from academia, public sector in terms of government and administration, to a rapidly innovating private sector in technology and other industries. Roles typically involve researching various aspects of computer networks, artificial intelligence, and distributed computing, similar to the research topics you encounter in the IEEE Transactions on Network Science and Engineering. However, if you are interested in handling and nurturing young minds, teaching can also be a viable option. For instance, those with a foundational understanding in these disciplines can qualify to become preschool teachers, focusing on introducing children to the basics of science and engineering. One of the ways to do this is to meet the {anchor} specific to your state; in this case, Minnesota. Whether you're an aspiring teacher, a network scientist, or a distributed systems engineer, acquiring the right academic background and gaining applicable experience are key steps in starting a journey towards these professions.