Recent trends and future directions of congestion management strategies for routing in IoT-based wireless sensor network: a thematic review

The rapid expansion of the Internet of Things (IoT) has paved the way for the development of smart systems, with Wireless Sensor Networks (WSNs) serving as the underlying infrastructure. While it exists in a miniature form, IoT-based WSN today stands as the revolution of the future, promising tremendous influence on society. However, the limited resources of these networks pose various challenges, particularly in routing, with congestion being a significant issue that affects their efficiency. Although previous studies are available on congestion management in WSNs, research specifically focused on IoT-based WSNs and addressing the root causes of congestion is none. In order to address this gap, this article conducts a thematic review of the current literature to identify congestion management strategies and forecast future trends. The search identified 86 studies, among which 47 articles were analyzed. The six final themes were discovered: artificial intelligence approach, customized classical method, hybrid approach, cross-layering approach, SDN-based approach, and RPL routing advancement. The findings establish a comprehensive taxonomy model as a conceptual framework for future research in congestion management strategies for IoT-based WSNs routing. This taxonomy aids academic researchers as well as industrial practitioners and highlights crucial areas for future research on congestion issues from the perspective of Industry 4.0. © 2024, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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