English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The demand for an efficient Jhult tolerance system has led to the development of complex monitoring infrastructure, which in turn has created an overwhelming task of data and event management. The increasing level of details at the hardware and software layer clearly afects the scalability and peijbrmance of monitoring and management tools. In this paper, we propose a problem notiJication framework that directly addresses the issue of monitor scalability. We first present the design and inzpIementation of our step-by-step approach to analyzing, filtering, and clas,slfiing the plethora of node statistics. Then, we present experimental results to show that our approach only needs minimal system resource and thus has low overhead. Finally, we introduce our web-based cluster management system that provides hardware controls at both cluster and nodal levels.

IPMI-based Efficient Notification Framework for Large Scale Cluster Computing