Fluid Composition of Intermittent IoT Energy Services
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Abstract (arXiv)
We propose a novel fluid composition approach of wireless energy services in a crowdsourced IoT environment. The proposed approach selects an optimal set of dynamic energy services according to the consumer's requirements. We leverage the mobility patterns of the crowd in confined areas to capture the intermittent behavior of IoT energy services. We model the IoT energy services based on their mobility patterns to propose a knapsack-based heuristic for the fluid composition. Experimental results demonstrate the efficiency of the proposed approach.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Aug 2020.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1.
2 papers.
- 2021Spatiotemporal Data Mining: A Survey on Challenges and Open Problemscited by 13
- 2023Energy Loss Prediction in IoT Energy Servicescited by 0
- 2023Energy Loss Prediction in IoT Energy Services16 May 2023
- 2021Spatiotemporal Data Mining: A Survey on Challenges and Open Problems31 Mar 2021