Strategic bandwidth allocation for QoS in IoT gateway: predicting future needs based on IoT device habits

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dc.contributor.authorChakour, Imane
dc.contributor.authorDaoui, Cherki
dc.contributor.authorBaslam, Mohamed
dc.contributor.authorSainz de Abajo, Beatriz
dc.contributor.authorGarcía-Zapirain, Begoña
dc.date.accessioned2025-05-14T08:15:18Z
dc.date.available2025-05-14T08:15:18Z
dc.date.issued2024-01-08
dc.date.updated2025-05-14T08:15:18Z
dc.description.abstractThe Internet of Things (IoT) is evolving, driven by the increasing demand for bandwidth. A key focus is on minimizing communication delays. This paper introduces a new solution called Predictive Dynamic Bandwidth Allocation (PDBA), using adaptive predictive algorithms in the IoT context. The approach involves predicting resource needs and network conditions, allowing for efficient bandwidth allocation. The PDBA framework uses advanced predictive algorithms to foresee bandwidth requirements for IoT devices at specific intervals, contributing to low communication latency - crucial for responsive IoT applications.To handle dynamic changes in the IoT environment, like device connectivity fluctuations during sleep mode transitions, our framework incorporates a dynamic perceptual algorithm inspired by reinforcement learning principles. This real-time adaptation mitigates the impact of environmental fluctuations, ensuring consistently low latency. Simulations across various IoT scenarios demonstrate the PDBA framework's effectiveness. The adaptive predictive algorithm significantly improves latency by nearly 10%, reduces packet loss to 6.8%, and increases throughput to 94.2% compared to traditional methods, with notably lower computing times of 0.69 seconds. These results underscore PDBA's potential to enhance Quality of Service (QoS) in IoT networks. The article provides a comprehensive examination of the PDBA framework's components, its seamless integration into the IoT environment, and its substantial role in optimizing communication performance within IoT networksen
dc.description.sponsorshipThis work was supported by the eVida Research Group, University of Deusto, Bilbao, Spain, under Grant IT 905-16en
dc.identifier.citationChakour, I., Daoui, C., Baslam, M., Sainz-De-Abajo, B., & Garcia-Zapirain, B. (2024). Strategic bandwidth allocation for QoS in IoT gateway: predicting future needs based on IoT device habits. IEEE Access, 12, 6590-6603. https://doi.org/10.1109/ACCESS.2024.3351111
dc.identifier.doi10.1109/ACCESS.2024.3351111
dc.identifier.eissn2169-3536
dc.identifier.urihttps://hdl.handle.net/20.500.14454/2745
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rights© 2024 The Authors
dc.subject.otherAdaptive predictive algorithms
dc.subject.otherBandwidth allocation
dc.subject.otherCommunication latency
dc.subject.otherIoT networks
dc.subject.otherPredictive dynamic bandwidth allocation (PDBA)
dc.titleStrategic bandwidth allocation for QoS in IoT gateway: predicting future needs based on IoT device habitsen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage6603
oaire.citation.startPage6590
oaire.citation.titleIEEE Access
oaire.citation.volume12
oaire.licenseConditionhttps://creativecommons.org/licenses/by-nc-nd/4.0/
oaire.versionVoR
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