Mobile Ad-Hoc Network (MANET) Method: Some Trends and Open Issues
DOI:
https://doi.org/10.59511/riestech.v3i2.108Keywords:
Bibliometrics, MANET, Vosviewer, VisualizationAbstract
This study analyzes the latest developments and trends in the field of Mobile Ad-Hoc Networks (MANET) through a bibliometric approach using a metadata dataset from publications taken from Scopus between 2021 and 2024. By utilizing VOSviewer to visualize the data, the study identified key keywords that dominated the MANET literature, such as "security", "routing protocols", "mobility", and "5G". The visualization results show several important clusters, including topics related to network security, vehicle networks (VANET), and the application of advanced technologies such as machine learning in network management. Despite the decline in the number of publications in 2023 and 2024, collaboration between authors continues to show a strong trend. The research also highlights various challenges that are still open problems, such as the development of efficient routing protocols, improving network security, and managing resources in a dynamic MANET environment. In addition to the VOSviewer analysis, further exploration was carried out using the built-in visualization tools from the Scopus web platform to enrich the interpretation of emerging topics and research connections. This was followed by a deeper conceptual mapping using Scopus AI, which provided a visual breakdown of interconnected themes such as security issues, routing protocols, and different network types like VANET and FANET. To complement and validate the findings, the study also incorporated evidence based summaries retrieved from Consensus.app, offering additional insights from AI-driven scientific consensus. This multi-platform approach enhances the reliability of the analysis and provides a more comprehensive view of current and future research directions in the MANET domain.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Authors retain copyright of their articles. All articles published in RiESTech are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Anyone may share and adapt the work, including for commercial purposes, provided that appropriate credit is given to the authors and the journal, a link to the license is provided, and any changes are indicated. License details: https://creativecommons.org/licenses/by/4.0/

