6533b873fe1ef96bd12d5725
RESEARCH PRODUCT
A data aggregation strategy based on wavelet for the internet of things
Laura RicciAndrea De SalveBarbara Guidisubject
IoTExploitRange query (data structures)Computer science0102 computer and information sciences02 engineering and technologyFog Computingcomputer.software_genre01 natural sciencesWaveletSoftwareSearch algorithmHistogramComputational Theory and Mathematic0202 electrical engineering electronic engineering information engineeringP2PSettore INF/01 - Informaticabusiness.industry020206 networking & telecommunicationsData aggregation; Fog Computing; IoT; P2P; Range query; WaveletData aggregationData aggregator010201 computation theory & mathematicsComputational MathematicRange queryData miningbusinesscomputerWireless sensor networkWaveletSoftwaredescription
The advent of emerging information and communication technologies, such as RFID, small size sensors and sensor networks, has made accessible a huge amount of information that requires sophisticated and efficient search algorithms to support queries on that data. In this paper we focus on the problem of aggregating data collected from these devices to efficiently support queries, inferences or statistics on them. In general, data aggregation techniques are necessary to efficiently collect information in a compact and cost-effective way. Some current solutions try to meet the above criteria, by exploiting different data aggregation techniques, for instance BitVector or Q_Digest. In this manuscript, we exploit the mathematical wavelet structure to define a sophisticated data aggregation technique for information collected from different nodes. The aggregated data is then exploited for solving multi-dimensional range queries. Experimental results based on simulations of a real dataset show the effectiveness of our approach with respect to other aggregation strategies.
year | journal | country | edition | language |
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2017-09-01 |