Information Retrieval for IoT and WoT: State-of-the-Art, Taxonomy Framework, and Evolutionary Directions
The explosive growth of Internet of Things (IoT) and Web of Things (WoT) technologies, characterized by a vast diversity of devices and data formats, producing vast volumes of information at a high pace in real time necessitates a paradigm shift in information retrieval (IR) systems. Traditional IR struggles to navigate the dynamic landscapes of these interconnected environments. This work proposes a multidimensional taxonomy framework to bridge this critical gap. Our framework not only unifies existing classification approaches but also delves into the analysis of traditional IR subtasks, thereby establishing a cohesive foundation for future advancements in IR tailored to the evolving IoT/WoT landscape. We further contribute by identifying key challenges and posing open research questions, thus propelling the development of next-generation IR techniques specifically tailored to the intricate search demands of the evolving IoT and WoT cyber-world.
Authors
- Juan M. Fernández‐Luna (ORCID: https://orcid.org/0000-0002-0366-4545)
- Annalina Caputo (ORCID: https://orcid.org/0000-0002-7144-8545)
- Cristyan Manta-Caro (ORCID: https://orcid.org/0000-0002-5011-9355)
Institutions
- Universidad de Granada (ES)
- Dublin City University (IE)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2024-12-25
- DOI
- https://doi.org/10.1109/jiot.2024.3522219
- Citations
- 1
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- Universidad de Granada