L. Loven et al., "Towards EDISON: An Edge-Native Approach to Distributed Interpolation of Environmental Data," 2019 28th International Conference on Computer Communication and Networks (ICCCN), Valencia, Spain, 2019, pp. 1-6, https://doi.org/10.1109/ICCCN.2019.8847121
Towards EDISON : an edge-native approach to distributed interpolation of environmental data
|Author:||Lovén, Lauri1; Peltonen, Ella1; Pandya, Abhinay1;|
1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020042119552
IEEE Computer Society Press,
|Publish Date:|| 2020-04-21
Prevalent weather prediction methods are based on sensor data, collected by satellites and a sparse grid of stationary weather stations. Various initiatives improve the prediction models by including additional data sources such as mobile weather sensors, mobile phones, and wireless sensor networks (WSN) of, for example, smart homes. The underlying computing paradigm is predominantly centralized, with all data collected and analyzed in the cloud. This solution is not scalable. When the spatial and temporal density of weather sensor data grows, the required data transmission capacities and computational resources become unfeasible. We identify the challenges posed by spatial distribution of a weather prediction model, and suggest solutions for those challenges. We propose EDISON: an edge-native interpolation approach based on AI methods, distributed horizontally on edge servers. Finally, we demonstrate EDISON with a simple, simulated setup.
Proceedings. International Conference on Computer Communications and Networks
|Pages:||1 - 6|
28th International Conference on Computer Communications and Networks, ICCCN 2019, 29 July - 1 Aug 2019 Valencia, Spain
International Conference on Computer Communications and Networks
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
This research is supported by the Academy of Finland 6Genesis Flagship (grant 318927) program, the MEC-AI project, funded by the Future Makers program of Jane and Aatos Erkko Foundation and Technology Industries of Finland Centennial Foundation, by the EU Horizon 2020 project CUTLER: Coastal Urban developmenT through the LEnses of Resiliency, under contract no. 770469 (http://www.cutlerh2020.eu/), and the personal grant for Lauri Lovén on Edgenative AI research by the Tauno Tönning foundation.
|EU Grant Number:||
(770469) CUTLER - Coastal Urban developmenT through the LEnses of Resiliency
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
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