Skip to Main content Skip to Navigation
Conference papers

Distributed Sampling Storage for Statistical Analysis of Massive Sensor Data

Abstract : Cyber-physical systems interconnect the cyber world with the physical world in which sensors are massively networked to monitor the physical world. Various services are expected to be able to use sensor data reflecting the physical world with information technology. Given this expectation, it is important to simultaneously provide timely access to massive data and reduce storage costs. We propose a data storage scheme for storing and querying massive sensor data. This scheme is scalable by adopting a distributed architecture, fault-tolerant even without costly data replication, and enables users to efficiently select multi-scale random data samples for statistical analysis. We implemented a prototype system based on our scheme and evaluated its sampling performance. The results show that the prototype system exhibits lower latency than a conventional distributed storage system.
Complete list of metadata

Cited literature [8 references]  Display  Hide  Download

https://hal.inria.fr/hal-01542469
Contributor : Hal Ifip <>
Submitted on : Monday, June 19, 2017 - 5:01:48 PM
Last modification on : Thursday, March 5, 2020 - 4:47:37 PM
Long-term archiving on: : Friday, December 15, 2017 - 8:53:45 PM

File

978-3-642-32498-7_18_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Hiroshi Sato, Hisashi Kurasawa, Takeru Inoue, Motonori Nakamura, Hajime Matsumura, et al.. Distributed Sampling Storage for Statistical Analysis of Massive Sensor Data. International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES), Aug 2012, Prague, Czech Republic. pp.233-243, ⟨10.1007/978-3-642-32498-7_18⟩. ⟨hal-01542469⟩

Share

Metrics

Record views

184

Files downloads

256