| Title | Perspectives on Anomaly and Event Detection in Exascale Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Iuhasz, Gabriel, Petcu, Dana |
| Conference Name | 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS) |
| Date Published | may |
| Keywords | Anomaly, anomaly detection framework, Big Data, Big Data methods, compositionality, computer network reliability, distributed, event detection, exascale, exascale systems, global overview, HPC, machine learning, Monitoring, parallel processing, Predictive Metrics, pubcrawl, resilience, Scientific Computing Security, security of data |
| Abstract | The design and implementation of exascale system is nowadays an important challenge. Such a system is expected to combine HPC with Big Data methods and technologies to allow the execution of scientific workloads which are not tractable at this present time. In this paper we focus on an event and anomaly detection framework which is crucial in giving a global overview of a exascale system (which in turn is necessary for the successful implementation and exploitation of the system). We propose an architecture for such a framework and show how it can be used to handle failures during job execution. |
| DOI | 10.1109/BigDataSecurity-HPSC-IDS.2019.00051 |
| Citation Key | iuhasz_perspectives_2019 |
Perspectives on Anomaly and Event Detection in Exascale Systems