Quality of Experience Optimization in IoT Energy Services
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Abstract (arXiv)
We propose a novel Quality of Experience (QoE) metric as a key criterion to optimize the composition of energy services in a crowdsourced IoT environment. A novel importance-based composition algorithm is proposed to ensure the highest QoE for consumers. A set of experiments is conducted to evaluate the proposed approaches' effectiveness and efficiency.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Aug 2022.
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Citing papers per year: 2022: 2; 2023: 3.
5 papers.
- 2023Monitoring Efficiency of IoT Wireless Chargingcited by 2
- 2022IMAP: Individual huMAn mobility Patterns visualizing platformcited by 1
- 2022DIY-IPS: Towards an Off-the-Shelf Accurate Indoor Positioning Systemcited by 0
- 2023Energy Loss Prediction in IoT Energy Servicescited by 0
- 2023CrowdWeb: A Visualization Tool for Mobility Patterns in Smart Citiescited by 0
- 2023CrowdWeb: A Visualization Tool for Mobility Patterns in Smart Cities22 May 2023
- 2023Energy Loss Prediction in IoT Energy Services16 May 2023
- 2023Monitoring Efficiency of IoT Wireless Charging10 Mar 2023
- 2022IMAP: Individual huMAn mobility Patterns visualizing platform8 Sep 2022
- 2022DIY-IPS: Towards an Off-the-Shelf Accurate Indoor Positioning System8 Sep 2022