Big data management for periodic wireless sensor networks. (Gestion de données volumineuses dans les réseaux de capteurs périodiques)
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Summary
This thesis proposes novel big data management techniques for periodic sensor networksembracing the limitations imposed by wsn and the nature of sensor data, and proposes a multiple level activity model that uses behavioral functions modeled by modified Bezier curves to define application classes and allow sampling adaptive rate.
- Type
- preprint
- Published
- 2014-06-30
- Cited by
- 2
- References
- 100
- Access
- Open access
- OpenAlex
- https://openalex.org/W78684558
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:203989259
Keywords
Wireless sensor network, Computer science, Aperiodic graph, Node (physics), Data mining
References
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- SPATIAL INTERPOLATION OF WEATHER VARIABLES FOR SINGLE LOCATIONS USING ARTIFICIAL NEURAL NETWORKS
- A Tree Projection Algorithm for Generation of Frequent Item Sets
- Adaptive stream resource management using Kalman Filters
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