In order to meet stringent performance requirements, system administrators must effectively
detect undesirable performance behaviours, identify potential root causes, and take …

Cloud computing has become increasingly popular by obviating the need for users to own
and maintain complex computing infrastructures. However, due to their inherent complexity …

When a system fails to function properly, health-related data are collected for
troubleshooting. However, it is challenging to effectively identify anomalies from the …

This work presents models characterizing failures observed during the execution of large
scientific applications on Amazon EC2. Scientific workflows are used as the underlying …

Scientific workflows are an enabler of complex scientific analyses. Large-scale scientific
workflows are executed on complex parallel and distributed resources, where many things …

To monitor and diagnose bottlenecks on network paths used for large-scale data transfers,
there is an increasing trend to deploy measurement frameworks such as perfSONAR. These …

Anomaly detection is a challenging problem, mainly due to the lack of a sufficient set of
abnormal samples that represents every possible anomaly. Therefore unsupervised …

While improving the performance, nonblocking communication is prone to synchronization
errors between MPI applications and the underlying MPI libraries. Such synchronization …

Data‐intensive applications have attracted considerable attention in recent years. Business
organizations are increasingly becoming data‐driven and therefore look for novel ways to …

Microservice architecture has been widely adopted in large-scale applications. However, it
also brings new challenges to ensuring reliable performance and maintenance due to the …