DocumentCode
2005236
Title
Scalable data fusion using Astrolabe
Author
Birman, Kenneth P. ; Van Renesse, Robbert ; Vogels, Werner
Author_Institution
Cornell Univ., Ithaca, NY, USA
Volume
2
fYear
2002
fDate
8-11 July 2002
Firstpage
1434
Abstract
The dramatic growth of computer networks creates both an opportunity and a daunting distributed computing problem for users seeking to perform data fusion and data mining. The problem is that data often resides on large numbers of devices and evolves rapidly. Systems that collect data at a single location scale poorly and suffer from single-point-failures. Astrolabe performs data fusion in real-time, creating a virtual system-wide hierarchical database, which evolves as the underlying information changes. A scalable aggregation mechanism offers a flexible way to perform data mining within the resulting virtual database. Astrolabe is secure, robust under a wide range of failure and attack scenarios, and imposes low loads even under stress.
Keywords
data mining; database management systems; distributed processing; real-time systems; sensor fusion; attack scenarios; computer networks; data collection; data mining; distributed computing; distributed computing problem; hierarchical databases; low loads; peer-to-peer communication; real-time data fusion; scalable aggregation mechanism; scalable data fusion; single-point failures; virtual system-wide hierarchical database; Application software; Biosensors; Data mining; Data security; Databases; Distributed computing; Peer to peer computing; Protocols; Robustness; Scalability;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion, 2002. Proceedings of the Fifth International Conference on
Conference_Location
Annapolis, MD, USA
Print_ISBN
0-9721844-1-4
Type
conf
DOI
10.1109/ICIF.2002.1020984
Filename
1020984
Link To Document