Browsing Faculty of Engineering by Subject "Big data"
Now showing items 1-4 of 4
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A big data processing framework for self-healing internet of things applications
(IEEE, 2016)In this study, we introduce a big data processing framework that provides self-healing capability in the Internet of Things domain. We discuss the high-level architecture of this framework and its prototype implementation. ... -
DILAF: A framework for distributed analysis of large-scale system logs for anomaly detection
(Wiley, 2019-02)System logs constitute a rich source of information for detection and prediction of anomalies. However, they can include a huge volume of data, which is usually unstructured or semistructured. We introduce DILAF, a framework ... -
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ... -
Incremental analysis of large-scale system logs for anomaly detection
(IEEE, 2019)Anomalies during system execution can be detected by automated analysis of logs generated by the system. However, large scale systems can generate tens of millions of lines of logs within days. Centralized implementations ...
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