Impact Conflict Detection of IoT Services in Multi-resident Smart Homes
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866911898529693696 |
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| author | Chaki, Dipankar Bouguettaya, Athman Lakhdari, Abdallah |
| author_facet | Chaki, Dipankar Bouguettaya, Athman Lakhdari, Abdallah |
| contents | We propose a novel impact conflict detection framework for IoT services in multi-resident smart homes. The proposed impact assessment model is developed based on the integral of a signal deviation strategy. We mine the residents' previous service usage records to design a robust preference estimation model. We design an impact conflict detection approach using temporal proximity and preferential proximity techniques. Experimental results on real-world datasets demonstrate the effectiveness of the proposed approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_00277 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Impact Conflict Detection of IoT Services in Multi-resident Smart Homes Chaki, Dipankar Bouguettaya, Athman Lakhdari, Abdallah Distributed, Parallel, and Cluster Computing We propose a novel impact conflict detection framework for IoT services in multi-resident smart homes. The proposed impact assessment model is developed based on the integral of a signal deviation strategy. We mine the residents' previous service usage records to design a robust preference estimation model. We design an impact conflict detection approach using temporal proximity and preferential proximity techniques. Experimental results on real-world datasets demonstrate the effectiveness of the proposed approach. |
| title | Impact Conflict Detection of IoT Services in Multi-resident Smart Homes |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2406.00277 |