Browse

A Scalable and Flexible Repository for Big Sensor Data

Cited 6 time in Web of Science Cited 8 time in Scopus
Issue Date
2015
Publisher
Institute of Electrical and Electronics Engineers
Citation
IEEE Sensors Journal, vol.15 no.12, pp. 7284-7294
Keywords
Big data archivingdata compressionquality-adjustable sensor datastorage managementwireless
sensor network
Abstract
Data generation rates of sensors are rapidly increasing, reaching a limit such that storage expansion cannot keep up with the data growth. We propose a new big data archiving scheme that handles the huge volume of sensor data with an optimized lossy coding. Our scheme leverages spatial and temporal correlations inherent in typical sensor data. The spatiotemporal correlations, observed in quality adjustable sensor data, enable us to compress a massive amount of sensor data without compromising distinctive attributes in sensor signals. Sensor data fidelity can also be decreased gradually. In order to maximize storage efficiency, we derive an optimal storage configuration for this data aging scenario. Experiments show outstanding compression ratios of our scheme and the optimality of storage configuration that minimizes system-wide distortion of sensor data under a given storage space.
Language
English
URI
https://hdl.handle.net/10371/95479
DOI
https://doi.org/10.1109/JSEN.2015.2471802
Files in This Item:
There are no files associated with this item.
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Computer Science and Engineering (컴퓨터공학부)Journal Papers (저널논문_컴퓨터공학부)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse