Title
A Heterogeneous Fault-Resilient Architecture for Mining Anomalous Activity Patterns in Smart Homes
Abstract
We are presenting a massively parallel heterogeneous cloud-based architecture oriented towards anomalous activity detection in smart homes. The architecture has very high resilience to both hardware and software faults, it is capable of collecting activity from various data sources and performing anomaly detection in real-time. We corroborate the approach with an efficient checkpointing mechanism for data processing which allows the implementation of hybrid (CPU/GPU) fault-resilience and anomaly detection through pattern mining techniques, at the same time offering high throughput.
Year
DOI
Venue
2015
10.1007/978-3-319-19713-5_12
INTERNATIONAL JOINT CONFERENCE: CISIS'15 AND ICEUTE'15
Keywords
Field
DocType
Anomaly detection,Pattern mining,Smart home,Fault resiliency,Heterogeneous architecture,Graphics processing unit
Anomaly detection,Data mining,Data processing,Massively parallel,Computer science,Home automation,Software,Throughput,Graphics processing unit,Cloud computing,Distributed computing
Conference
Volume
ISSN
Citations 
369
2194-5357
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Ciprian Pungila1114.51
Bogdan Manate2203.44
Viorel Negru331147.71