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@@ -8,6 +8,16 @@ @incollection{chapter2025xai
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chapter = 2,
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}
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@article{202504.0090,
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arxiv = {https://doi.org/10.20944/preprints202504.0090.v1},
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year = 2025,
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month = {April},
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publisher = {Preprints},
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author = {Oliver Robert Fox and Giacomo Bergami and Graham Morgan},
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title = {Verified Language Processing with Hybrid Explainability},
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journal = {Preprints}
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}
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@Article{ai6040071,
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AUTHOR = {Appleby, Samuel and Bergami, Giacomo and Ushaw, Gary},
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bibtex_show = {true},
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ABSTRACT = {To the best of our knowledge, we offer the first IoT-Osmotic simulator supporting 6G and Cloud infrastructures, leveraging the similarities in Software-Defined Wide Area Network (SD-WAN) architectures when used in Osmotic architectures and User-Centric Cell-Free mMIMO (massive multiple-input multiple-output) architectures. Our simulator acts as a simulator orchestrator, supporting the interaction with a patient digital twin generating patient healthcare data (vital signs and emergency alerts) and a VANET simulator (SUMO), both leading to IoT data streams towards the cloud through pre-initiated MQTT protocols. This contextualises our approach within the healthcare domain while showcasing the possibility of orchestrating different simulators at the same time. The combined provision of these two aspects, joined with the addition of a ring network connecting all the first-mile edge nodes (i.e., access points), enables the definition of new packet routing algorithms, streamlining previous solutions from SD-WAN architectures, thus showing the benefit of 6G architectures in achieving better network load balancing, as well as showcasing the limitations of previous approaches. The simulated 6G architecture, combined with the optimal routing algorithm and MEL (Microelements software components) allocation policy, was able to reduce the time required to route all communications from IoT devices to the cloud by up to 50.4% compared to analogous routing algorithms used within 5G architectures.},
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DOI = {10.3390/s25051591},
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arxiv = {https://www.preprints.org/manuscript/202502.0523/v1}
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c = {https://www.preprints.org/manuscript/202502.0523/v1}
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}
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