Paper Info
Title
A multimodel based range query processing algorithm for information collection in CPS
Abstract
AbstractA multimodel based range query processing algorithm is proposed to solve the information collection task for the CPSs, which utilizes multiple probability models to depict the data distribution of a sensor node. The execution of the multimodel based algorithm consists of two phases, which are the preprocessing phase and the query processing phase. During the preprocessing phase, multiple models are constructed for each node according to their historical data. During the query processing phase, a suitable model is selected from the multiple models with the help of a sampling based algorithm, which is used to process the query. As the multimodel based algorithm needs to sample data from the network, it can waste energy more than that of the single model based algorithm in some cases, which does not sample data from the network. The cost of the multimodel based and single model based algorithm is analyzed. A cost model based algorithm is proposed to select a better algorithm to process a query from the two algorithms. Experimental results show that the cost model based algorithm can save 13.3% energy consumption more than that of the single model based algorithm.
Year
DOI
Venue
2015
10.1155/2015/403267
Periodicals
Field
DocType
Volume
Sensor node,Data mining,Computer science,Range query (data structures),Algorithm,FSA-Red Algorithm,Preprocessor,Sampling (statistics),Energy consumption,Population-based incremental learning,Multiple Models
Journal
2015
Issue
ISSN
Citations 
1
1550-1329
1
PageRank 
References 
Authors
0.35
17
6
Name
Order
Citations
PageRank
Guilin Li1116.09
Xing Gao2158.37
Longjiang Guo317726.73
Juncong Lin410520.73
ying gao510.35
Minghong Liao69018.97