DocumentCode :
1956989
Title :
Clustering Analysis for the Management of Self-Monitoring Device Networks
Author :
Quiroz, Andres ; Parashar, Manish ; Gnanasambandam, Nathan ; Sharma, Naveen
Author_Institution :
CAIP Center, Rutgers Univ., Piscataway, NJ
fYear :
2008
fDate :
2-6 June 2008
Firstpage :
55
Lastpage :
64
Abstract :
The increasing computing and communication capabilities of multi-function devices (MFDs) have enabled networks of such devices to provide value-added services. This has placed stringent QoS requirements on the operations of these device networks. This paper investigates how the computational capabilities of the devices in the network can be harnessed to achieve self-monitoring and QoS management. Specifically, the paper investigates the application of clustering analysis for detecting anomalies and trends in events generated during device operation, and presents a novel decentralized cluster and anomaly detection algorithm. The paper also describes how the algorithm can be implemented within a device overlay network, and demonstrates its performance and utility using simulated as well as real workloads.
Keywords :
computer network management; quality of service; statistical analysis; telecommunication security; QoS management; QoS requirements; anomaly detection algorithm; clustering analysis; decentralized cluster algorithm; multifunction devices; self-monitoring device network management; value-added services; Clustering algorithms; Computer network management; Computer networks; Conference management; Data analysis; Event detection; Laboratories; Monitoring; Software systems; Storage automation; anomaly detection; clustering; device networks; self-monitoring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Autonomic Computing, 2008. ICAC '08. International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-0-7695-3175-5
Electronic_ISBN :
978-0-7695-3175-5
Type :
conf
DOI :
10.1109/ICAC.2008.30
Filename :
4550827
Link To Document :
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