Two-level energy-efficient data reduction strategies based on SAX-LZW and hierarchical clustering for minimizing the huge data conveyed on the internet of things networks.
Ali Kadhum M. Al-QurabatSuha Abdulhussein AbdulzahraAli Kadhum IdreesPublished in: J. Supercomput. (2022)
Keyphrases
- hierarchical clustering
- energy efficient
- data reduction
- huge data
- data compression
- wireless sensor networks
- clustering algorithm
- energy consumption
- sensor networks
- compression algorithm
- big data
- clustering method
- data analysis
- compression ratio
- feature selection
- base station
- network structure
- preprocessing
- data mining
- energy efficiency
- k means
- knowledge discovery
- rough set theory
- routing protocol
- classification accuracy
- classification rules
- model selection
- social networks
- mobile devices
- computer networks
- sensor nodes
- decision making
- data quality
- data structure
- image quality
- dimensionality reduction
- mobile computing