FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments

In the rapidly evolving landscape of the Internet of Things (IoT), managing the vast volumes of data generated by connected devices presents significant challenges, particularly in B5G IoT environments. One key issue is data redundancy, where identical data is stored several times because it is capt...

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Main Authors: Bruno Ramos-Cruz, Francisco J. Quesada-Real, Javier Andreu-Pérez, Jessica Zaqueros-Martinez
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Future Internet
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Online Access:https://www.mdpi.com/1999-5903/17/7/295
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author Bruno Ramos-Cruz
Francisco J. Quesada-Real
Javier Andreu-Pérez
Jessica Zaqueros-Martinez
author_facet Bruno Ramos-Cruz
Francisco J. Quesada-Real
Javier Andreu-Pérez
Jessica Zaqueros-Martinez
author_sort Bruno Ramos-Cruz
collection DOAJ
description In the rapidly evolving landscape of the Internet of Things (IoT), managing the vast volumes of data generated by connected devices presents significant challenges, particularly in B5G IoT environments. One key issue is data redundancy, where identical data is stored several times because it is captured by multiple sensors. To address this, we introduce “<i>FODIT</i>”, a filter-based module designed to optimize data storage in IoT systems. FODIT leverages probabilistic data structures, specifically filters, to improve storage efficiency and query performance. We hypothesize that applying these structures can significantly reduce redundancy and accelerate data access in resource-constrained IoT deployments. We validate our hypothesis through targeted simulations under a specific and rare configuration: high-frequency and high-redundancy environments, with controlled duplication rates between 4% and 8%. These experiments involve data storage in local databases, cloud-based systems, and distributed ledger technologies (DLTs). The results demonstrate FODIT’s ability to reduce storage requirements and improve query responsiveness under these stress-test conditions. Furthermore, the proposed approach has broader applicability, particularly in DLT-based environments such as blockchain, where efficient querying remains a critical challenge. Nonetheless, some limitations remain, especially regarding the current data structure used to maintain consistency with the DLT, and the need for further adaptation to real-world contexts with dynamic workloads. This research highlights the potential of filter-based techniques to improve data management in IoT and blockchain systems, contributing to the development of more scalable and responsive infrastructures.
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spelling doaj-art-b2853080e0db4e95a4868e0ff26dc97c2025-08-20T02:45:34ZengMDPI AGFuture Internet1999-59032025-06-0117729510.3390/fi17070295FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT EnvironmentsBruno Ramos-Cruz0Francisco J. Quesada-Real1Javier Andreu-Pérez2Jessica Zaqueros-Martinez3Computer Science Department, University of Jaen, 23071 Jaén, SpainComputer Science Department, University of Jaen, 23071 Jaén, SpainCentre for Computational Intelligencer, School of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UKComputer Science Department, University of Jaen, 23071 Jaén, SpainIn the rapidly evolving landscape of the Internet of Things (IoT), managing the vast volumes of data generated by connected devices presents significant challenges, particularly in B5G IoT environments. One key issue is data redundancy, where identical data is stored several times because it is captured by multiple sensors. To address this, we introduce “<i>FODIT</i>”, a filter-based module designed to optimize data storage in IoT systems. FODIT leverages probabilistic data structures, specifically filters, to improve storage efficiency and query performance. We hypothesize that applying these structures can significantly reduce redundancy and accelerate data access in resource-constrained IoT deployments. We validate our hypothesis through targeted simulations under a specific and rare configuration: high-frequency and high-redundancy environments, with controlled duplication rates between 4% and 8%. These experiments involve data storage in local databases, cloud-based systems, and distributed ledger technologies (DLTs). The results demonstrate FODIT’s ability to reduce storage requirements and improve query responsiveness under these stress-test conditions. Furthermore, the proposed approach has broader applicability, particularly in DLT-based environments such as blockchain, where efficient querying remains a critical challenge. Nonetheless, some limitations remain, especially regarding the current data structure used to maintain consistency with the DLT, and the need for further adaptation to real-world contexts with dynamic workloads. This research highlights the potential of filter-based techniques to improve data management in IoT and blockchain systems, contributing to the development of more scalable and responsive infrastructures.https://www.mdpi.com/1999-5903/17/7/295B5G IoTfiltersdata storage
spellingShingle Bruno Ramos-Cruz
Francisco J. Quesada-Real
Javier Andreu-Pérez
Jessica Zaqueros-Martinez
FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
Future Internet
B5G IoT
filters
data storage
title FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
title_full FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
title_fullStr FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
title_full_unstemmed FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
title_short FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments
title_sort fodit a filter based module for optimizing data storage in b5g iot environments
topic B5G IoT
filters
data storage
url https://www.mdpi.com/1999-5903/17/7/295
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AT franciscojquesadareal foditafilterbasedmoduleforoptimizingdatastorageinb5giotenvironments
AT javierandreuperez foditafilterbasedmoduleforoptimizingdatastorageinb5giotenvironments
AT jessicazaquerosmartinez foditafilterbasedmoduleforoptimizingdatastorageinb5giotenvironments