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FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems (2012)
| Venue: | In Proceedings of the 16th International Conference On Principles Of Distributed Systems (OPODIS |
| Citations: | 6 - 2 self |
BibTeX
@INPROCEEDINGS{Anceaume12fixme:a,
author = {Emmanuelle Anceaume and Erwan Le Merrer and Romaric Ludinard and Gilles Straub},
title = {FixMe: A Self-organizing Isolated Anomaly Detection Architecture for Large Scale Distributed Systems},
booktitle = {In Proceedings of the 16th International Conference On Principles Of Distributed Systems (OPODIS},
year = {2012},
pages = {1--15}
}
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Abstract
Abstract. Monitoring a system is the ability of collecting and analyzing relevant information provided by the monitored devices so as to be continuously aware of the system state. However, the ever growing complexity and scale of systems makes both real time monitoring and fault detection a quite tedious task. Thus the usually adopted option is to focus solely on a subset of information states, so as to provide coarse-grained indicators. As a consequence, detecting isolated failures or anomalies is a quite challenging issue. In this work, we propose to address this issue by pushing the monitoring task at the edge of the network. We present a peer-to-peer based architecture, which enables nodes to adaptively and efficiently self-organize according to their “health ” indicators. By exploiting both temporal and spatial correlations that exist between a device and its vicinity, our approach guarantees that only isolated anomalies (an anomaly is isolated if it impacts solely a monitored device) are reported on the fly to the network operator. We show that the end-to-end detection process, i.e., from the local detection to the management operator reporting, requires a logarithmic number of messages in the size of the network. 1
Keyphrases
large scale distributed system self-organizing isolated anomaly detection architecture monitored device coarse-grained indicator tedious task information state network operator challenging issue local detection logarithmic number end-to-end detection process health indicator system state fault detection isolated failure management operator reporting monitoring task real time monitoring relevant information spatial correlation isolated anomaly
