activity incidents on distributed computing infrastructures

Distributed computing infrastructures are commonly used through scientic gateways, but operating these gateways requires important human intervention to handle operational incidents. This paper presents a self-healing process that quanties incident degrees of workow activities from metrics measuring long-tail eect, application eciency, data transfer issues, and site-specic problems. These metrics are simple enough to be computed online and they make little assumptions on the application or resource characteristics. From their degree, incidents are classied in levels and associated to sets of healing actions that are selected based on association rules modeling correlations between incident levels. We specically study the long-tail eect issue, and propose a new algorithm to control task replication. The healing process is parametrized on real application traces acquired in production on the European Grid Infrastructure. Experimental results obtained in the Virtual Imaging Platform show that the proposed method speeds up execution up to a factor of 4, consumes up to 26% less resource time than a control execution and properly detects unrecoverable errors.