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In traditional IoT architecture, several heterogeneous data streams from connected nodes are transmitted through gateways to the remote mobile cloud servers. The entire procedure is time\u2010 and energy\u2010consuming if the target dataset is comparatively small and uninterrupted. Also, using this conventional technique, the reliability grade drops significantly to meet additional security\u2010related quality of service (QoS) requirements compared to the service cost. We propose a quality of experience\u2010aware task rescheduling model using edge modules that offer territory\u2010based three\u2010layered edge IoT data analysis and service selection. The observation module at the application layer takes a near\u2010optimal remark upon each usage metric having distinct QoS components. Meanwhile, the QoS manager at the network layer handles network traffic due to the load associated with heterogeneous service needs. The precision of the knowledge is assured to the service manager through the sensing layer with few adaptability characteristics towards assorted service requests. The proposed three\u2010layered energy\u2010efficient model helps minimize data delivery time with minimal cost and optimized quality assurance for service\u2010based IoT infrastructures like smart agriculture, patient monitoring, and student monitoring.<\/jats:p>","DOI":"10.1155\/dsn\/5573818","type":"journal-article","created":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T07:35:12Z","timestamp":1748331312000},"source":"Crossref","is-referenced-by-count":2,"title":["Quality of Experience Aware Service Selection Model to Empower Edge Computing in IoT"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7480-3020","authenticated-orcid":false,"given":"Bipasha","family":"Guha Roy","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7194-6950","authenticated-orcid":false,"given":"Deepsubhra","family":"Guha 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